What Jobs are available for Machine Learning Engineer in Chicago?

This is a Hybrid role (2 days/week in office)
**Role Overview**
We are seeking a highly analytical and technically proficient Senior ML/AI Engineer to join our ARC team. This role is ideal for someone with a strong foundation in mathematics, statistics, and programming, and a passion for applying AI to solve complex financial problems. You will work to develop AI/ML/DS features for enterprise-wide AI products to develop models, optimize strategies, and contribute to the evolution of our AI-powered financial systems.
**What will you do:**
+ Design and develop machine learning models (Supervised, Unsupervised, and Reinforcement Learning), AI (Generative Models and Agent Orchestration) models, and Deep Learning models (e.g., Neural Networks and autoencoders).
+ Run Machine Learning tests and experiments.
+ Train and retrain systems to prevent drift and optimize results.
+ Solve complex problems with multi-layered data sets, extend existing ML frameworks (Scikit-Learn, XGBoost, Tensorflow) and AI frameworks (Keras, LangChain).
+ Leverage and develop advanced analytics models (network based, forecasting, rules-based), implement said algorithms, and build tools to apply them.
+ Turn structured, semi-structured and unstructured data into useful information
+ Lead development of ML/AI algorithms to analyze huge volumes of historical data to derive insights, make decisions, and form predictions.
+ Run tests, perform statistical analysis, and interpret test results
+ Develops prediction systems and machine learning algorithms.
+ Research and evaluate additional technologies and tools for developing innovative data solutions for business stakeholders i.e. What if analysis (forecasting, next-best-step), Domain Adaptation and Transfer forecasting, Temporal Convolutional Networks, long-term short-term, pricing models, Autoregressive Models.
**What you need to succeed:**
+ Master's or Ph.D. in Mathematics, Statistics, Computer Science, Data Science, Physics, AI, Machine Learning or a related field.
+ Leadership experience driving initiatives related to AI/GenAI/ML assets.
+ Experience in model development (ML/ Data Science, AI/GenAI) within financial services or technology sectors.
+ Proficiency in Python and SQL, TensorFlow, PyTorch, XGBoost, Scikit-learn
+ Strong grasp of Artificial Intelligence and Machine Learning frameworks and stacks.
+ Strong conceptual grasp and applied experience using Hypergraph Scenario Engine and Network based Methods (graph-based modeling tool that maps relationships between entities and simulates cascading scenarios).
+ Exposure to Quant Machine Learning tailored to quantitative finance, driving more accurate forecasting, risk modeling, pricing, and portfolio optimization, Chatbots (i.e., Distribution).
+ Familiarity with cloud platforms (AWS, Azure, GCP) and CI/CD pipelines is advantageous
+ Intellectual curiosity and adaptability to emerging AI and quant finance trends.
+ Strong communication skills to explain complex models to non-technical stakeholders.
+ Ability to work independently and collaboratively in a fast-paced, multidisciplinary environment.
+ Attention to detail and a rigorous approach to model validation and testing.
**Salary:**
$122,400.00 - $228,000.00
**Pay Type:**
Salaried
The above represents BMO Financial Group's pay range and type.
Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group's expected target for the first year in this position.
BMO Financial Group's total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: Us**
At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.
As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one - for yourself and our customers. We'll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we'll help you gain valuable experience, and broaden your skillset.
To find out more visit us at is proud to be an equal employment opportunity employer. We evaluate applicants without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other legally protected characteristics. We also consider applicants with criminal histories, consistent with applicable federal, state and local law.
BMO is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please send an e-mail to and let us know the nature of your request and your contact information.
Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

This is a Hybrid role (2 days/week in office)
**Role Overview**
We are seeking a highly analytical and technically proficient Senior ML/AI Engineer to join our ARC team. This role is ideal for someone with a strong foundation in mathematics, statistics, and programming, and a passion for applying AI to solve complex financial problems. You will work to develop AI/ML/DS features for enterprise-wide AI products to develop models, optimize strategies, and contribute to the evolution of our AI-powered financial systems.
**What will you do:**
+ Design and develop Machine Learning models (Supervised, Unsupervised, and Reinforcement Learning), AI (Generative models and Agent Orchestration) models, and Deep Learning models (e.g., Neural Networks and autoencoders).
+ Run Machine Learning tests and experiments.
+ Train and retrain systems to prevent drift and optimize results.
+ Solve complex problems with multi-layered data sets, extend existing ML frameworks (Scikit-Learn, XGBoost, Tensorflow) and AI frameworks (Keras, LangChain).
+ Leverage and develop advanced analytics models (network based, forecasting, rules-based), implement said algorithms, and build tools to apply them.
+ Turn structured, semi-structured and unstructured data into useful information
+ Develop ML/AI algorithms to analyze huge volumes of historical data to derive insights, make decisions, and form predictions.
+ Run tests, perform statistical analysis, and interpret test results
+ Establish the main functions of the digital foundations: (Hypergraph) Scenario Engine and Network based Methods: graph-based modeling tool that maps relationships between entities and simulates cascading scenarios
+ Exposure to Quant Machine Learning tailored to quantitative finance, driving more accurate forecasting, risk modeling, pricing, and portfolio optimization; Chatbots (i.e., Distribution)
+ Use analysis to provide recommendations and advice for business leaders to maintain to maintain market competitiveness.
+ Provide guidance (scoring, decisioning) in areas such as Multi-Objective optimization, safe RL and decision support, network propagation algorithms, entity resolution, clustering.
**What you need to succeed:**
+ Master's or Ph.D. in Mathematics, Statistics, Computer Science, Data Science, Physics, AI, Machine Learning or a related field.
+ Leadership experience driving initiatives related to AI/GenAI/ML assets
+ Experience in model development (ML/ Data Science, AI/GenAI) within financial services or technology sectors
+ Proficiency in Python and SQL, TensorFlow, PyTorch, XGBoost, Scikit-learn
+ Strong grasp of Artificial Intelligence and Machine Learning frameworks and stacks.
+ Familiarity with cloud platforms (AWS, Azure, GCP) and CI/CD pipelines is advantageous
+ Intellectual curiosity and adaptability to emerging AI and quant finance trends.
+ Strong communication skills to explain complex models to non-technical stakeholders.
+ Ability to work independently and collaboratively in a fast-paced, multidisciplinary environment.
+ Attention to detail and a rigorous approach to model validation and testing
**Salary:**
$122,400.00 - $228,000.00
**Pay Type:**
Salaried
The above represents BMO Financial Group's pay range and type.
Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group's expected target for the first year in this position.
BMO Financial Group's total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: Us**
At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.
As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one - for yourself and our customers. We'll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we'll help you gain valuable experience, and broaden your skillset.
To find out more visit us at is proud to be an equal employment opportunity employer. We evaluate applicants without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other legally protected characteristics. We also consider applicants with criminal histories, consistent with applicable federal, state and local law.
BMO is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please send an e-mail to and let us know the nature of your request and your contact information.
Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

Location: Anywhere in Country
At EY, we're all in to shape your future with confidence.
We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
**Technology - Data and Decision Science - AI Native Engineering**
*** **AI/Machine Learning Engineer, Senior Consultant**
**The opportunity**
Our Artificial Intelligence and Data team helps apply cutting edge technology and techniques to bring solutions to our clients. As part of that, you'll sit side-by-side with clients and diverse teams from EY to create a well-rounded approach to advising and solving challenging problems, some of which have not been solved before. No two days will be the same, and with constant research and development, you'll find yourself building knowledge that can be applied across a wide range of projects now, and in the future. You'll need to have a passion for continuous learning, stay ahead of the trends, and influence new ways of working so you can position solutions in the most relevant and innovative way for our clients. You can expect heavy client interaction in a fast-paced environment and the opportunity to develop your own career path for your unique skills and ambitions.
As a Senior AI Native Engineer, you will be at the forefront of revolutionizing how businesses leverage artificial intelligence. Your role will involve researching, building, and implementing scalable AI systems that learn and make predictions tailored to diverse business environments, whether in the cloud or on-premises. You will enhance data pipelines to ensure data integrity and optimize learning processes, all while collaborating with a talented team of data and analytics professionals.
**Your key responsibilities**
In this role, you will contribute significantly to the delivery of innovative AI solutions. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
You will spend your time on key responsibilities that include:
+ Researching and implementing scalable AI systems that meet business requirements.
+ Enhancing data pipelines and storage for optimal data accuracy and cleanliness.
+ Monitoring and optimizing learning processes to improve high-performance models.
+ This position may have travel requirements as needed to engage with external clients regularly.
**Skills and attributes for success**
To excel in this role, you will need a blend of technical expertise and interpersonal skills. Your ability to navigate complex challenges and deliver impactful solutions will be essential.
This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services.
+ Strong analytical and decision-making skills to guide project direction.
+ Proven experience in project management and tracking deliverable completion.
+ Ability to build and maintain relationships with clients and team members.
+ Excellent communication skills to convey complex ideas effectively.
**To qualify for the role, you must have**
+ A Bachelor's degree required (4-year degree).
+ 3-6 years of full-time working experience in AI and/or Machine Learning
+ Strong skills in Python.
+ Experience using Generative AI models and frameworks e.g. OpenAI family, open source LLMs, Dall-e, LlamaIndex, Langchain, Retrieval Augmented Generation (RAG).
+ Experience working with popular ML packages such as scikit-learn, Pytorch and ONNX, or related ML libraries.
+ Extensive experience using DevOps tools like GIT, Azure Devops and Agile tools such as Jira to develop and deploy analytical solutions with multiple features, pipelines, and releases.
+ A solid understanding of Machine Learning (ML) workflows including ingesting, analysing, transforming data and evaluating results to make meaningful predictions.
+ Experience with MLOps methods and platforms such as MLFlow.
+ Experience with CI/CD and test-driven development.
+ Experience designing, building, and maintaining ML models, frameworks, and pipelines.
+ Experience designing and deploying end to end ML workflows on at least one major cloud computing platform.
+ Understanding of data structures, data modelling and software engineering best practices.
+ Proficiency using data manipulation tools and libraries such as SQL, Pandas, and Spark.
+ Clearly communicating findings, recommendations, and opportunities to improve data systems and solutions.
+ Experience with containerization and scaling models.
+ Integrating models and feedback from downstream consumption systems - reporting and dashboards, AI driven applications.
+ Proficiency in deep learning techniques.
+ Strong foundation in mathematics, statistics, and operations research.
+ Experience with machine learning algorithms and data architecture design.
+ Familiarity with cloud computing and technical design optimization.
+ Knowledge of natural language processing and image processing techniques.
+ Understanding of continuous integration and deployment methodologies.
+ Experience in scaling models for various applications.
+ Strong mathematical and quantitative skills including calculus, linear algebra, and statistics.
+ Willingness to travel to meet client obligations.
**Ideally, you'll also have**
+ Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field.
+ Experience in hybrid collaboration and emotional agility.
+ A track record of working with diverse teams to drive outcomes through complex problem-solving.
+ Knowledge of sustainability practices in technology.
+ A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them.
+ Strong skills in languages beyond Python: R, JavaScript, Java, C++, C.
+ Experience fine-tuning Generative AI models.
**What we look for**
We seek individuals who are not only technically proficient but also possess the qualities of a top performer. You should be innovative, adaptable, and purpose driven by a desire to make a significant impact in the field of artificial intelligence. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
#FY26NATAID
#FY26NATAID
**What we offer you**
At EY, we'll develop you with future-focused skills and equip you with world-class experiences. We'll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more .
+ We offer a comprehensive compensation and benefits package where you'll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $105,800 to $74,800. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is 127,100 to 198,600. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
+ Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.
+ Under our flexible vacation policy, you'll decide how much vacation time you need based on your own personal circumstances. You'll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
**Are you ready to shape your future with confidence? Apply today.**
EY accepts applications for this position on an on-going basis.
For those living in California, please click here for additional information.
EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.
**EY | Building a better working world**
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law. 
EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY's Talent Shared Services Team (TSS) or email the TSS at .

Location: Anywhere in Country
At EY, we're all in to shape your future with confidence.
We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
**Technology - Data and Decision Science - AI Native Engineering**
*** **AI/Machine Learning Engineer, Manager Consultant**
**The opportunity**
Our Artificial Intelligence and Data team helps apply cutting edge technology and techniques to bring solutions to our clients. As part of that, you'll sit side-by-side with clients and diverse teams from EY to create a well-rounded approach to advising and solving challenging problems, some of which have not been solved before. No two days will be the same, and with constant research and development, you'll find yourself building knowledge that can be applied across a wide range of projects now, and in the future. You'll need to have a passion for continuous learning, stay ahead of the trends, and influence new ways of working so you can position solutions in the most relevant and innovative way for our clients. You can expect heavy client interaction in a fast-paced environment and the opportunity to develop your own career path for your unique skills and ambitions.
In this role, you will research, build, and implement scalable artificial intelligence systems that learn and make predictions tailored to business requirements across various environments, including cloud and on-premises. You will enhance data pipelines and storage, ensuring data is clean, accurate, and optimized for XOps processes. Additionally, you will monitor and evaluate learning processes to continuously improve high-performance models, collaborating with other data and analytics professionals to industrialize analysis into effective analytics solutions.
**Your key responsibilities**
As a Manager in AI Native Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver the latest data science and big data technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure data science solutions are properly engineered and maintained to support the ongoing business needs of our clients.
You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.
**Your responsibilities will include:**
+ Leading workstream delivery and ensuring the effective management of processes and projects.
+ Continuously improving processes by identifying innovative solutions through research and analysis.
+ Managing professional employees and supervising teams to deliver complex technical initiatives, with accountability for performance and results.
+ Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure.
+ Identifying opportunities for additional services and managing engagement economics.
**Skills and attributes for success**
To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services
The following attributes will make a significant impact:
+ Proven ability to develop solutions to complex problems and recommend changes to policies and procedures.
+ Strong judgment in selecting methods and techniques for obtaining results.
+ Experience in managing client relationships and delivering high-quality service.
+ Ability to lead teams effectively and manage change within the organization.
**To qualify for the role, you must have**
+ A Bachelor's degree required (4-year degree).
+ 6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
+ 2-4 years of experience directly managing technical teams
+ Strong skills in Python.
+ Experience using Generative AI models and frameworks e.g. OpenAI family, open source LLMs, Dall-e, LlamaIndex, Langchain, Retrieval Augmented Generation (RAG).
+ Experience working with popular ML packages such as scikit-learn, Pytorch and ONNX, or related ML libraries.
+ Extensive experience using DevOps tools like GIT, Azure Devops and Agile tools such as Jira to develop and deploy analytical solutions with multiple features, pipelines, and releases.
+ A solid understanding of Machine Learning (ML) workflows including ingesting, analysing, transforming data and evaluating results to make meaningful predictions.
+ Experience with MLOps methods and platforms such as MLFlow.
+ Experience with CI/CD and test-driven development.
+ Experience designing, building, and maintaining ML models, frameworks, and pipelines.
+ Experience designing and deploying end to end ML workflows on at least one major cloud computing platform.
+ Understanding of data structures, data modelling and software engineering best practices.
+ Proficiency using data manipulation tools and libraries such as SQL, Pandas, and Spark.
+ Clearly communicating findings, recommendations, and opportunities to improve data systems and solutions.
+ Experience with containerization and scaling models.
+ Integrating models and feedback from downstream consumption systems - reporting and dashboards, AI driven applications.
+ Deep Learning expertise.
+ Proficiency in Mathematics, Statistics, and Operations Research.
+ Experience with Machine Learning techniques.
+ Knowledge of Data Architecture Design and Modelling.
+ Familiarity with Cloud Computing environments.
+ Skills in Technical Design Optimization.
+ Experience with Continuous Integration and Continuous Delivery/Deployment.
+ Understanding of Natural Language Processing and Generation.
+ Knowledge in Image Processing and Analysis.
+ Skills in Speech and Audio Processing and Analysis.
+ Ability to scale models effectively.
+ Strong relationship-building skills.
+ Demonstrated client trust and value.
+ Effective communication skills with impact.
+ Digital fluency and emotional agility.
+ Experience in hybrid collaboration.
+ Commercial acumen and negotiation skills.
+ Proven ability to lead teams and manage change.
+ Strong mathematical and quantitative skills including calculus, linear algebra, and statistics.
+ Willingness to travel to meet client obligations.
**Ideally, you'll also have**
+ A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them.
+ Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field.
+ Experience working with diverse teams to deliver complex solutions.
+ Strong skills in languages beyond Python: R, JavaScript, Java, C++, C.
+ Experience fine-tuning Generative AI models.
+ Experience in managing complex projects with multiple stakeholders.
+ A strong understanding of industry trends and emerging technologies.
+ Skills in data visualization and storytelling with data.
**What we look for**
We seek individuals who are not only technically proficient but also possess the ability to think critically and creatively. Top performers demonstrate a commitment to excellence, a collaborative spirit, and a passion for driving innovation in the field of AI and data science. Your ability to collaborate effectively and communicate with clarity will set you apart as a leader in our team.
#FY26NATAID
#FY26NATAID
**What we offer you**
At EY, we'll develop you with future-focused skills and equip you with world-class experiences. We'll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more .
+ We offer a comprehensive compensation and benefits package where you'll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $124,300 to $27,900. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is 149,200 to 259,000. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
+ Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.
+ Under our flexible vacation policy, you'll decide how much vacation time you need based on your own personal circumstances. You'll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
**Are you ready to shape your future with confidence? Apply today.**
EY accepts applications for this position on an on-going basis.
For those living in California, please click here for additional information.
EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.
**EY | Building a better working world**
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.
Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.
EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law. 
EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY's Talent Shared Services Team (TSS) or email the TSS at .

Description
Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI)? Excited by using massive amounts of disparate data to develop AI/ML models? Eager to learn to apply AI/ML to a diverse array of enterprise use? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world's AI technology?
The Amazon Web Services Professional Services (ProServe) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the ML project lifecycle.
Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer. You'll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.
Key job responsibilities
As an experienced technology professional, you will be responsible for:
1. Implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring.
2. Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads.
3. Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable.
4. Collaborating with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models.
5. Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
6. Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts.
7. Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies.
This is a customer-facing role with potential travel to customer sites as needed.
Basic Qualifications
- 3+ years cloud architecture and implementation
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience
- 5+ years data, software, or ML engineering, with strong understanding of distributed computing. (e.g., data pipelines, training and inference, ML infrastructure design)
- 3+ years developing predictive modeling, natural language processing, and deep learning, with a proven track record of building and deploying ML models on cloud. (e.g., Amazon SageMaker or similar)
- 3+ years developing with SQL, Python, and at least one additional programming language (e.g., Java, Scala, JavaScript, TypeScript). Proficient with leading ML libraries and frameworks (e.g., TensorFlow, PyTorch)
Preferred Qualifications
- AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, Step Functions, VPC, CloudFormation)
- AWS Professional certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional)
- Experience with automation (e.g., Terraform, Python), Infrastructure as Code (e.g., CloudFormation, CDK), and Containers & CI/CD Pipelines.
- Knowledge of common security and compliance standards (e.g., HIPAA, GDPR)
- Strong communication skills with ability to explain complex concepts to technical and non-technical audiences
- Experience building ML pipelines with MLOps best practices, including: data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, and retraining
- Experience with MLOps (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,200/year in our lowest geographic market up to $204,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit . This position will remain posted until filled. Applicants should apply via our internal or external career site.

Description
Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI)? Excited by using massive amounts of disparate data to develop AI/ML models? Eager to learn to apply AI/ML to a diverse array of enterprise use? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world's AI technology?
The Amazon Web Services Professional Services (ProServe) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the ML project lifecycle. You will lead customer-focused project teams as a technical leader, and perform hands-on development of ML solutions with exceptional quality
Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer. You'll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.
Key job responsibilities
Key job responsibilities
As an experienced technology professional, you will be responsible for:
1. Leading project teams and implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring.
2. Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads.
3. Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable.
4. Collaborating with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models.
5. Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
6. Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts.
7. Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies.
This is a customer-facing role with potential travel to customer sites as needed.
About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture - Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth - We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Basic Qualifications
- 5+ years cloud architecture and implementation
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience
- 8+ years leading technical teams and hands-on experience focused on data, software, or ML engineering, with strong understanding of distributed computing. (e.g., data pipelines, training and inference, ML infrastructure design)
- 5+ years developing predictive modeling, natural language processing, and deep learning, with a proven track record of building and deploying ML models on cloud. (e.g., Amazon SageMaker or similar)
- 5+ years developing with SQL, Python, and at least one additional programming language (e.g., Java, Scala, JavaScript, TypeScript). Proficient with leading ML libraries and frameworks (e.g., TensorFlow, PyTorch)
Preferred Qualifications
- AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, Step Functions, VPC, CloudFormation)
- AWS Professional certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional)
- Experience with automation (e.g., Terraform, Python), Infrastructure as Code (e.g., CloudFormation, CDK), and Containers & CI/CD Pipelines.
- Knowledge of common security and compliance standards (e.g., HIPAA, GDPR)
- Strong communication skills with ability to explain complex concepts to technical and non-technical audiences with the ability to lead technical teams in customer projects
- Experience building ML pipelines with MLOps best practices, including: data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, and retraining
- Experience with MLOps (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $138,200/year in our lowest geographic market up to $239,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit . This position will remain posted until filled. Applicants should apply via our internal or external career site.

Description
Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI)? Excited by using massive amounts of disparate data to develop AI/ML models? Eager to learn to apply AI/ML to a diverse array of enterprise use? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world's AI technology?
The Amazon Web Services Professional Services (ProServe) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the ML project lifecycle. You will lead customer-focused project teams as a technical leader, and perform hands-on development of ML solutions with exceptional quality
Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer. You'll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.
Key job responsibilities
Key job responsibilities
As an experienced technology professional, you will be responsible for:
1. Leading project teams and implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring.
2. Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads.
3. Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable.
4. Collaborating with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models.
5. Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
6. Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts.
7. Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies.
This is a customer-facing role with potential travel to customer sites as needed.
About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture - Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth - We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Basic Qualifications
- 5+ years cloud architecture and implementation
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience
- 8+ years leading technical teams and hands-on experience focused on data, software, or ML engineering, with strong understanding of distributed computing. (e.g., data pipelines, training and inference, ML infrastructure design)
- 5+ years developing predictive modeling, natural language processing, and deep learning, with a proven track record of building and deploying ML models on cloud. (e.g., Amazon SageMaker or similar)
- 5+ years developing with SQL, Python, and at least one additional programming language (e.g., Java, Scala, JavaScript, TypeScript). Proficient with leading ML libraries and frameworks (e.g., TensorFlow, PyTorch)
Preferred Qualifications
- AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, Step Functions, VPC, CloudFormation)
- AWS Professional certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional)
- Experience with automation (e.g., Terraform, Python), Infrastructure as Code (e.g., CloudFormation, CDK), and Containers & CI/CD Pipelines.
- Knowledge of common security and compliance standards (e.g., HIPAA, GDPR)
- Strong communication skills with ability to explain complex concepts to technical and non-technical audiences with the ability to lead technical teams in customer projects
- Experience building ML pipelines with MLOps best practices, including: data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, and retraining
- Experience with MLOps (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $138,200/year in our lowest geographic market up to $239,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit . This position will remain posted until filled. Applicants should apply via our internal or external career site.

Description
Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI)? Excited by using massive amounts of disparate data to develop AI/ML models? Eager to learn to apply AI/ML to a diverse array of enterprise use? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world's AI technology?
The Amazon Web Services Professional Services (ProServe) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the ML project lifecycle.
Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer. You'll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.
Key job responsibilities
Key job responsibilities
As an experienced technology professional, you will be responsible for:
1. Implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring.
2. Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads.
3. Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable.
4. Collaborating with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models.
5. Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
6. Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts.
7. Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies.
This is a customer-facing role with potential travel to customer sites as needed.
About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture - Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth - We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Basic Qualifications
- 3+ years cloud architecture and implementation
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience
- 5+ years data, software, or ML engineering, with strong understanding of distributed computing. (e.g., data pipelines, training and inference, ML infrastructure design)
- 3+ years developing predictive modeling, natural language processing, and deep learning, with a proven track record of building and deploying ML models on cloud. (e.g., Amazon SageMaker or similar)
- 3+ years developing with SQL, Python, and at least one additional programming language (e.g., Java, Scala, JavaScript, TypeScript). Proficient with leading ML libraries and frameworks (e.g., TensorFlow, PyTorch)
Preferred Qualifications
- AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, Step Functions, VPC, CloudFormation)
- AWS Professional certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional)
- Experience with automation (e.g., Terraform, Python), Infrastructure as Code (e.g., CloudFormation, CDK), and Containers & CI/CD Pipelines.
- Knowledge of common security and compliance standards (e.g., HIPAA, GDPR)
- Strong communication skills with ability to explain complex concepts to technical and non-technical audiences
- Experience building ML pipelines with MLOps best practices, including: data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, and retraining
- Experience with MLOps (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,200/year in our lowest geographic market up to $204,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit . This position will remain posted until filled. Applicants should apply via our internal or external career site.

Description
Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intelligence (AI) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Generative AI (GenAI)? Excited by using massive amounts of disparate data to develop AI/ML models? Eager to learn to apply AI/ML to a diverse array of enterprise use? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world's AI technology?
The Amazon Web Services Professional Services (ProServe) team is seeking a skilled ML Engineer to join our team as a Delivery Consultant at Amazon Web Services (AWS). In this role, you'll work closely with customers to design, implement, and manage AWS AI/ML and GenAI solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their cloud journey, providing technical expertise and best practices throughout the ML project lifecycle.
Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure AI/ML and GenAI solutions tailored to meet the specific needs of each customer. You'll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.
Key job responsibilities
Key job responsibilities
As an experienced technology professional, you will be responsible for:
1. Implementing end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring.
2. Designing and implementing machine learning pipelines that support high-performance, reliable, scalable, and secure ML workloads.
3. Designing scalable ML solutions and operations (MLOps) using AWS services and leveraging GenAI solutions when applicable.
4. Collaborating with cross-functional teams (Applied Science, DevOps, Data Engineering, Cloud Infrastructure, Applications) to prepare, analyze, and operationalize data and AI/ML models.
5. Serving as a trusted advisor to customers on AI/ML and GenAI solutions and cloud architectures
6. Sharing knowledge and best practices within the organization through mentoring, training, publication, and creating reusable artifacts.
7. Ensuring solutions meet industry standards and supporting customers in advancing their AI/ML, GenAI, and cloud adoption strategies.
This is a customer-facing role with potential travel to customer sites as needed.
About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture - Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth - We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Basic Qualifications
- 3+ years cloud architecture and implementation
- Bachelor's degree in Computer Science, Engineering, related field, or equivalent experience
- 5+ years data, software, or ML engineering, with strong understanding of distributed computing. (e.g., data pipelines, training and inference, ML infrastructure design)
- 3+ years developing predictive modeling, natural language processing, and deep learning, with a proven track record of building and deploying ML models on cloud. (e.g., Amazon SageMaker or similar)
- 3+ years developing with SQL, Python, and at least one additional programming language (e.g., Java, Scala, JavaScript, TypeScript). Proficient with leading ML libraries and frameworks (e.g., TensorFlow, PyTorch)
Preferred Qualifications
- AWS experience preferred, with proficiency in a range of AWS services (e.g., SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, Step Functions, VPC, CloudFormation)
- AWS Professional certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional)
- Experience with automation (e.g., Terraform, Python), Infrastructure as Code (e.g., CloudFormation, CDK), and Containers & CI/CD Pipelines.
- Knowledge of common security and compliance standards (e.g., HIPAA, GDPR)
- Strong communication skills with ability to explain complex concepts to technical and non-technical audiences
- Experience building ML pipelines with MLOps best practices, including: data preprocessing, model hosting, feature selection, hyperparameter tuning, distributed & GPU training, deployment, monitoring, and retraining
- Experience with MLOps (e.g., MLFlow, Kubeflow) and orchestration (e.g., Airflow, AWS Step Functions). Experience building applications using GenAI technologies (LLMs, Vector Stores, LangChain, Prompt Engineering)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,200/year in our lowest geographic market up to $204,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit . This position will remain posted until filled. Applicants should apply via our internal or external career site.