11,143 Machine Learning Engineer Engineering Data Science jobs in the United States
Senior Machine Learning Engineer/Machine Learning Engineer III
Posted 8 days ago
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Job Description
At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That's why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don't need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.
At Workday, we value our candidates' privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.
Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.
In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.
About the Team
It's fun to work in a company where people truly believe in what they're doing. At Workday, we're committed to bringing passion and customer focus to the business of enterprise applications. We work hard, and we're serious about what we do. But we like to have a good time, too. In fact, we run our company with that principle in mind every day: One of our core values is fun.
We're working on making machine learning core to Workday's products by building features and capabilities that can be scaled out to hundreds of use cases within Workday. Illuminate: The next generation of Workday AI is unlocking a whole new level of productivity and human potential by accelerating manual tasks, assisting every employee, and ultimately transforming entire business processes. With more than 70 million users under contract generating more than 800 billion transactions a year on our platform, Illuminate leverages the world's largest and cleanest HR and Finance dataset. The combination of this data-with Illuminate's ability to understand the context behind it-enables Workday to unlock value in a way no competitor can. Join us as we change the way millions of people work.
About the Role
As a machine learning engineer, you will help develop tailored user experiences using advanced LLMs, Knowledge Graphs, personalization, and predictive analysis. You will collaborate with other engineers to deliver ML solutions across Workday's product ecosystem and utilize software and data engineering stacks to enable training, deployment, and lifecycle management of various ML models. You will develop and deploy new products at scale and leverage Workday's vast computing resources on rich datasets to deliver transformative value to our customers.
In addition to contributing to feature and service development, you must have an approach of continuous improvement, passion for quality, scale, and security. You must be curious and prepared to question or challenge choices and practices where they don't make sense to you or could be improved. You also should have a product approach and strong intuition around how ML can drive a better customer experience. Lastly, a strong sense of ownership and teamwork are essential to succeed in this role.
Key Responsibilities:
- Own exploration, design and execution of advanced ML models, algorithms and frameworks that deliver value to our users.
- Apply machine learning techniques including LLMs, knowledge graphs, deep learning including generative models, natural language understanding, and named entity recognition to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud based machine learning architectures.
- Own the performance, scalability, metric based deployed evaluation, and ongoing data driven enhancements of your products.
- Keep abreast of the latest advancements in NLP research, techniques, and tools and apply this knowledge onto ML Features.
- Collaborate with a team of innovative engineers to deliver AI-powered agents that integrate deeply into HR and Financial workflows, accelerating intelligent decision making.
Senior Machine Learning Engineer:
Basic Qualifications:
- Bachelor's (Master's or PhD preferred) degree in engineering, computer science, physics, math or equivalent
- 5+ yrs experience as a member of a machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation
- 5+ years of professional experience with Python and supporting numeric libraries, with experience in shipping production code and models
- 3+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface
- 3+ years of professional experience in building services to host machine learning models in production at scale with cloud computing platforms (e.g. AWS, GCP, etc.)
- 3+ years of professional experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
Basic Qualifications
- 3+ yrs experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation
- 1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow
- 1+ years of professional experience in building services to host machine learning models in production at scale
- 1+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
- 1+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)
- Bachelor's (Master's or PhD preferred) degree in engineering, computer science, physics, math or equivalent
- Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
- Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases
- Professional experience in independently solving ambiguous, open-ended problems and technically leading teams
- Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders
- Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement
Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.
Primary Location: USA.CA.Pleasanton
Primary Location Base Pay Range: $198,400 USD - $97,600 USD
Additional US Location(s) Base Pay Range: 167,200 USD - 297,600 USD
Our Approach to Flexible Work
With Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!
Machine Learning Engineer
Posted 4 days ago
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Job Description
We are seeking a skilled Machine Learning Engineer to join our team. In this role, you will design, develop, and deploy machine learning models that solve real-world problems and drive business value. You’ll work closely with data scientists, software engineers, and product teams to build scalable, production-ready AI solutions.
Responsibilities
• Build, train, and deploy machine learning models and algorithms.
• Collect, preprocess, and analyze large datasets for modeling.
• Develop and maintain end-to-end ML pipelines (data ingestion → model training → deployment).
• Monitor and improve model accuracy, performance, and scalability.
• Collaborate with cross-functional teams to integrate ML solutions into products.
• Research and apply the latest ML/AI techniques and tools.
Qualifications
• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field (Master’s preferred).
• Strong programming skills in Python (plus experience with libraries such as TensorFlow, PyTorch, or scikit-learn).
• Solid understanding of statistics, probability, and algorithms.
• Experience deploying models in production (cloud platforms like AWS, Azure, or GCP preferred).
• Knowledge of data engineering tools, APIs, and version control (Git).
• Excellent problem-solving skills and ability to explain ML concepts to non-technical stakeholders.
What We Offer
• Competitive pay (salary/hourly depending on experience).
• Remote and flexible work options.
• Opportunities for professional growth and certifications.
• Innovative projects in a collaborative environment.
Company Details
Machine Learning Engineer
Posted 1 day ago
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Job Description
Lincoln Electric is the world leader in the engineering, design, and manufacturing of advanced arc welding solutions, automated joining, assembly and cutting systems, plasma and oxy-fuel cutting equipment, and has a leading global position in brazing and soldering alloys. Lincoln is recognized as the Welding Expert™ for its leading materials science, software development, automation engineering, and application expertise, which advance customers' fabrication capabilities to help them build a better world. Headquartered in Cleveland, Ohio, Lincoln Electric is a $4.2B publicly traded company (NASDAQ:LECO) with over 12,000 employees around the world, with operations in 71 manufacturing and automation system integration locations across 21 countries and maintains a worldwide network of distributors and sales offices serving customers in over 160 countries.
Location: Euclid - 22801
Employment Status: Salary Full-Time
Function: Engineering
Req ID: 26915
Summary
Lincoln Electric has an outstanding opportunity for a Machine Learning Engineer based at our Euclid, Ohio manufatcuring headquarters. As a Machine Learning Engineer (ML Engineer), you will be responsible for designing, developing, and implementing deep learning models to address various challenges in developing vision-based tools. You will work closely with cross-functional teams to integrate these models into our products and services, ensuring they meet performance and scalability requirements.
In addition to competitive pay, Lincoln Electric offers a lucrative profit-sharing plan, student loan repayment program PLUS tuition reimbursement, medical/dental/vision, 401(k) with company match, paid time off and many more outstanding benefits!
** This position has flexibility for hybrid work to be determined as approiate depending on business needs. Candidate must be able to work on-site in Euclid, OH as needed.**
What You Will Do
As an ML Engineer, you will play a key role in a new data science position to help us identify, diagnose, and cure production inefficiencies using data. Specific responsibilities include:
- Model Development : Design and develop deep learning models using frameworks such as TensorFlow, PyTorch, and Keras for specific applications in the manufacturing domain.
- Training and Evaluation : Train models on large datasets, evaluate their performance, and fine-tune hyperparameters to optimize results.
- Deployment : Implement and deploy models in production environments (including cloud-based deployments), ensuring they are scalable and efficient.
- Collaboration : Work with data scientists, software engineers, and product managers to integrate models into applications and services.
- Research : Stay up to date with the latest advancements in deep learning, transformers and graph neural networks and apply new techniques to new applications.
- Documentation : Maintain thorough documentation of model architecture, training processes, and evaluation metrics using ML Flow or equivalent.
Education & Experience Requirements
- Education : Bachelor's or Master’s degree in computer science, Electrical Engineering, or a related field. PhD is a plus.
- Experience : Proven experience (7+ years) in developing and deploying deep learning models. Experience with large-scale datasets and cloud platforms is preferred.
- Skills :
- Proficiency in deep learning frameworks and ability to design boutique neural networks with data augmentation and attention mechanisms.
- Ability to write professional software using SOLID programming principles and writing testing protocols for ML code.
- Working knowledge of using version control tools and principles to collaborate with other team members.
- Deep knowledge of partial differential equations, scientific computing and statistical methods.
- Soft Skills : Excellent problem-solving abilities, strong communication skills, and the ability to work collaboratively in a team environment.
Lincoln Electric is an Equal Opportunity Employer. We are committed to promoting equal employment opportunity for applicants, without regard to their race, color, national origin, religion, sex (including pregnancy, childbirth, or related medical conditions, including, but not limited to, lactation), sexual orientation, gender identity, age, veteran status, disability, genetic information, and any other category protected by federal, state, or local law.
Machine Learning Engineer
Posted today
Job Viewed
Job Description
Lincoln Electric is the world leader in the engineering, design, and manufacturing of advanced arc welding solutions, automated joining, assembly and cutting systems, plasma and oxy-fuel cutting equipment, and has a leading global position in brazing and soldering alloys. Lincoln is recognized as the Welding Expert™ for its leading materials science, software development, automation engineering, and application expertise, which advance customers' fabrication capabilities to help them build a better world. Headquartered in Cleveland, Ohio, Lincoln Electric is a $4.2B publicly traded company (NASDAQ:LECO) with over 12,000 employees around the world, with operations in 71 manufacturing and automation system integration locations across 21 countries and maintains a worldwide network of distributors and sales offices serving customers in over 160 countries.
Location: Euclid - 22801
Employment Status: Salary Full-Time
Function: Engineering
Req ID: 26915
Summary
Lincoln Electric has an outstanding opportunity for a Machine Learning Engineer based at our Euclid, Ohio manufatcuring headquarters. As a Machine Learning Engineer (ML Engineer), you will be responsible for designing, developing, and implementing deep learning models to address various challenges in developing vision-based tools. You will work closely with cross-functional teams to integrate these models into our products and services, ensuring they meet performance and scalability requirements.
In addition to competitive pay, Lincoln Electric offers a lucrative profit-sharing plan, student loan repayment program PLUS tuition reimbursement, medical/dental/vision, 401(k) with company match, paid time off and many more outstanding benefits!
** This position has flexibility for hybrid work to be determined as approiate depending on business needs. Candidate must be able to work on-site in Euclid, OH as needed.**
What You Will Do
As an ML Engineer, you will play a key role in a new data science position to help us identify, diagnose, and cure production inefficiencies using data. Specific responsibilities include:
- Model Development : Design and develop deep learning models using frameworks such as TensorFlow, PyTorch, and Keras for specific applications in the manufacturing domain.
- Training and Evaluation : Train models on large datasets, evaluate their performance, and fine-tune hyperparameters to optimize results.
- Deployment : Implement and deploy models in production environments (including cloud-based deployments), ensuring they are scalable and efficient.
- Collaboration : Work with data scientists, software engineers, and product managers to integrate models into applications and services.
- Research : Stay up to date with the latest advancements in deep learning, transformers and graph neural networks and apply new techniques to new applications.
- Documentation : Maintain thorough documentation of model architecture, training processes, and evaluation metrics using ML Flow or equivalent.
Education & Experience Requirements
- Education : Bachelor's or Master’s degree in computer science, Electrical Engineering, or a related field. PhD is a plus.
- Experience : Proven experience (7+ years) in developing and deploying deep learning models. Experience with large-scale datasets and cloud platforms is preferred.
- Skills :
- Proficiency in deep learning frameworks and ability to design boutique neural networks with data augmentation and attention mechanisms.
- Ability to write professional software using SOLID programming principles and writing testing protocols for ML code.
- Working knowledge of using version control tools and principles to collaborate with other team members.
- Deep knowledge of partial differential equations, scientific computing and statistical methods.
- Soft Skills : Excellent problem-solving abilities, strong communication skills, and the ability to work collaboratively in a team environment.
Lincoln Electric is an Equal Opportunity Employer. We are committed to promoting equal employment opportunity for applicants, without regard to their race, color, national origin, religion, sex (including pregnancy, childbirth, or related medical conditions, including, but not limited to, lactation), sexual orientation, gender identity, age, veteran status, disability, genetic information, and any other category protected by federal, state, or local law.
Machine Learning Engineer
Posted today
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Job Description
Lawrence Berkeley National Lab's (LBNL) NERSC Division has an opening for a Machine Learning Engineer to join the team.
In this exciting role, you will serve as a Machine Learning Engineer in NERSC's Data and AI Services group. We are building a next-generation platform for scientific AI on supercomputers. You will apply broad expertise to develop AI services to support science. You will be a part of multidisciplinary and cross-institution projects, involving lab, academic and industry partners. Responsibilities could include developing new AI services and supporting the AI software stack on NERSC supercomputers; deploying new cutting-edge tools and frameworks for at-scale scientific AI workflows; and working with scientists to apply AI techniques to their research.
The selected candidate(s) will be hired at the Computer Systems Engineer 3 or 4 (CSE3 or CSE4) depending on their level skills and experience. When applying, a cover letter is highly encouraged.
What You Will Do, at Level 3:
- Develop AI services on NERSC's advanced computing and data systems to support fundamental science
- Support the AI software stack on NERSC supercomputers, deploy new cutting-edge tools and frameworks for scalable AI workflows.
- Provide expert AI engineering engagement, and training events to scientists and users of NERSC computing resources.
- Engage with the AI community to stay on top of the latest advancements in AI services and software
- Shape future NERSC supercomputers, evaluating new architectures for AI.
- Collaborate with scientists and industry partners to enable transformative AI for science
- Determine methods and procedures on new assignments and may coordinate activities of other personnel.
- Network with key contacts outside your own area of expertise.
- Work on and resolve complex issues where analysis of situations or data requires an in-depth evaluation of variable factors.
- Exercise judgment in selecting methods, techniques and evaluation criteria for obtaining results.
- Mentor and lead early career staff members in AI services, techniques and projects
- Stay abreast of new and emerging trends in AI services, through collaborations, workshops and conferences; translate these new directions into actionable opportunities for NERSC or NERSC users.
- Develop strategy for addressing both performance, as well as productivity requirements of the NERSC AI for science community.
- Work on and resolve significant and unique issues where analysis of situations or data requires an evaluation of intangibles.
- Exercise independent judgment in methods, techniques and evaluation criteria for obtaining results.
- Bachelor's degree in Physical Sciences, Computer Science or related field or equivalent is required. Masters and PhD degrees in similar disciplines are preferred.
- Typically requires a minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or equivalent experience.
- Wide-ranging experience in the areas of AI and/or data science, as applied to scientific data.
- Ability to troubleshoot and resolve complex issues in creative and effective ways.
- Ability to network and collaborate with key contacts outside their own area of expertise.
- Excellent oral and written communication skills.
- Excellent software development skills
- Proven ability to work productively both independently and as part of an interdisciplinary team balancing divergent objectives involving research, code development, supporting software and consulting with scientists.
- Typically requires a minimum of 12 years of related experience with a Bachelor's degree; or 8 years and a Master's degree; or equivalent experience.
- Broad expertise and/or unique knowledge in the areas of AI technology is required.
- Ability to work on and resolve significant and unique issues where analysis of situations or data requires an evaluation of intangibles.
- Ability to exercise independent judgment in methods, techniques and evaluation criteria for obtaining results.
- Familiarity with deep learning architectures and technologies (e.g., TensorFlow, PyTorch, JAX).
- Track record of AI software development, AI service deployments, or publications in AI/science venues.
- Experience with GPUs and performance optimization of ML at scale.
- Familiarity with containerization and HPC workflows.
Notes:
- This is a full-time, career appointment, exempt (monthly paid) from overtime pay.
- This position will be hired at a level commensurate with the business needs and the skills, knowledge, and abilities of the successful candidate.
- Salary range
- Level 3: The full salary range of this position is between $136,440 to $30,244 per year and is expected to pay between a targeted range of 153,492 to 187,596 per year depending upon candidates' full skills, knowledge, and abilities, including education, certifications, and years of experience.
- Level 4: The full salary range of this position is between 155,388 to 262,224 per year and is expected to pay between a targeted range of 174,804 to 213,660 per year depending upon candidates' full skills, knowledge, and abilities, including education, certifications, and years of experience.
- This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
- This position requires substantial on-site presence, but is eligible for a flexible work mode, and hybrid schedules may be considered. Hybrid work is a combination of performing work on-site at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA and some telework. Individuals working a hybrid schedule must reside within 150 miles of Berkeley Lab. Work schedules are dependent on business needs. In rare cases, full-time telework or remote work modes may be considered. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites.
Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov
Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law.
Berkeley Lab is a University of California employer. It is the policy of the University of California to undertake affirmative action and anti-discrimination efforts, consistent with its obligations as a Federal and State contractor.
Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.
Machine Learning Engineer
Posted today
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Job Description
Summary:
Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page.
Required Skills:
Machine Learning Engineer Responsibilities:
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Research, design, develop, and test operating systems-level software, compilers, and network distribution software for massive social data and prediction problems.
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Have industry experience working on a range of ranking, classification, recommendation, and optimization problems, e.g. payment fraud, click-through or conversion rate prediction, click-fraud detection, ads/feed/search ranking, text/sentiment classification, collaborative filtering/recommendation, or spam detection.
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Work on problems of large scope, develop highly scalable systems, algorithms and tools leveraging deep learning, data regression, and rules based models.
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Suggest, collect, analyze and synthesize requirements and bottlenecks in technology, systems, and tools.
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Develop solutions that iterate with a higher efficiency, efficiently leverage orders of magnitude more data, and explore state-of-the-art deep learning techniques.
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Demonstrate strong engineering skills and require minimal guidance on engineering craft.
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Apply advanced machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
Minimum Qualifications:
Minimum Qualifications:
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Requires a Bachelor's degree (or foreign equivalent) in Computer Science, Engineering, Applied Sciences, Mathematics, Physics or related field.
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Requires completion of a university-level course, research project, internship, or thesis in the following:
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1.- Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow
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2.- Machine Learning Algorithms and their applications: recommendation systems, computer vision, natural language processing, or data mining
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3.- Translating insights into business recommendations
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4.- Hadoop, HBase, Pig, MapReduce, Sawzall, Bigtable, or Spark
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5.- Deep Neural Networks
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6.- Probability theory, Linear Algebra, Calculus, Data Analysis
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7.- Understanding of agile methodologies such as: Scrum, Kanban
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8.- Developing and debugging in C, C++, and Java
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9.- Scripting languages: Perl, Python, PHP, or shell scripts
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10.- Relational databases and SQL
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11.- Software development tools: Code editors (VIM or Emacs), and revision control systems (Subversion, GIT, or Perforce)
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12.- Linux, UNIX, or other *nix-like OS including file manipulation and simple commands
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13.- Distributed systems, including sharding, consistency, and availability
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14.- Building highly-scalable performant solutions
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15.- Data structures and Algorithms
Public Compensation:
$187,974/year to $200,200/year + bonus + equity + benefits
Industry: Internet
Equal Opportunity:
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at
Machine Learning Engineer
Posted 1 day ago
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Job Description
Companies want to train their own large models on their own data. The current industry standard is to train on a random sample of your data, which is inefficient at best and actively harmful to model quality at worst. There is compelling research showing that smarter data selection can train better models faster-we know because we did much of this research. Given the high costs of training, this presents a huge market opportunity. We founded DatologyAI to translate this research into tools that enable enterprise customers to identify the right data on which to train, resulting in better models for cheaper. Our team has pioneered deep learning data research, built startups, and created tools for enterprise ML. For more details, check out our recent blog posts sharing our high-level results for text models and image-text models.
We've raised over $57M in funding from top investors like Radical Ventures, Amplify Partners, Felicis, Microsoft, Amazon, and notable angels like Jeff Dean, Geoff Hinton, Yann LeCun and Elad Gil. We're rapidly scaling our team and computing resources to revolutionize data curation across modalities.
This role is based in Redwood City, CA. We are in office 4 days a week.
About the Role
We're looking for an experienced Machine Learning Engineer to join as a member of our core Datology AI team. As one of our early senior hires, you will partner closely with our founders on the direction of our product and drive business-critical technical decisions.
You will contribute to developing our core product, starting from the main data curation pipeline. These are key components of our stack that allow us to process customer data and apply state of the art research for identifying the most informative data points in large-scale datasets. You will have a broad impact over the technology, product, and our company's culture.
What You'll Work On
- Architect, build, and deploy the ML systems and services that power our data curation platform
- Design and implement large-scale data pipelines that curate datasets and make them ready for training cutting-edge models
- Partner with researchers and engineers to bring new features and research capabilities to our customers
- Ensure that our systems are reliable, secure, and worthy of our customers' trust
- 4+ years of experience
- Have meaningful experience with leading and building production ML systems and platforms that deliver on major product initiatives.
- Have a strong belief in the criticality of high-quality data and are highly motivated to work with the associated challenges
- Have experience and evidence of reading, understanding, and implementing ML research papers
- Proficiency in Python and in the most commonly used tools of the ML & Data Science ecosystem
- Experience maintaining a high-quality bar for design, correctness, and testing.
- Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed
- Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done
- Experience conducting open-ended research to improve the quality of collected data and running small scale ML experiments
Compensation
At DatologyAI, we are dedicated to rewarding talent with highly competitive salary and significant equity. The salary for this position ranges from $80,000 to 250,000.
- The candidate's starting pay will be determined based on job-related skills, experience, qualifications, and interview performance.
- 100% covered health benefits (medical, vision, and dental).
- 401(k) plan with a generous 4% company match.
- Unlimited PTO policy
- Annual 2,000 wellness stipend.
- Annual 1,000 learning and development stipend.
- Daily lunches and snacks are provided in our office!
- Relocation assistance for employees moving to the Bay Area.
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Machine Learning Engineer
Posted 1 day ago
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ABOUT THIS FEATURED OPPORTUNITY
The Machine Learning Engineer will join the team and develop and maintain a sophisticated chatbot system.
KEY SUCCESS FACTORS
- 3+ years of Machine Learning experience, with a specialization in NLP -related fields
- Text classification, named entity detection, embeddings
- Experience with LLMs and how they integrate into conversational AI systems
- Forecasting with Prophet
- Proficiency in Python
- Experience with AWS or GCP for deploying and managing machine learning models
Our benefits package includes:
- Comprehensive medical benefits
- Competitive pay
- 401(k) retirement plan
- .and much more!
About INSPYR Solutions
Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com.
INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, INSPYR Solutions complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities
Information collected and processed through your application with INSPYR Solutions (including any job applications you choose to submit) is subject to INSPYR Solutions' Privacy Policy and INSPYR Solutions' AI and Automated Employment Decision Tool Policy: By submitting an application, you are consenting to being contacted by INSPYR Solutions through phone, email, or text.
Machine Learning Engineer
Posted 2 days ago
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Job Description
Overview
Who we are
Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at Toyota. As one of the world’s most admired brands, Toyota is growing and leading the future of mobility through innovative, high-quality solutions designed to enhance lives and delight those we serve. We’re looking for talented team members who want to Dream. Do. Grow. with us.
To save time applying, Toyota does not offer sponsorship of job applicants for employment-based visas or any other work authorization for this position currently.
Who We're Looking For
Toyota’s Manufacturing Data & Tech Enablement team is on a mission to modernize and optimize our production systems through advanced analytics and AI-driven innovation. We are seeking a highly skilled Machine Learning Engineer to design, develop, and operationalize end-to-end machine learning pipelines that solve high-impact manufacturing problems. This role will be central to transforming large-scale data into actionable insights, enabling smarter decision-making on the shop floor, and supporting Toyota Production System (TPS) principles through technology.
The ideal candidate thrives at the intersection of manufacturing operations and cutting-edge AI, is capable of working autonomously, and is passionate about deploying scalable, maintainable, and production-ready ML solutions in a fast-paced, data-rich environment. The potential candidate applies data extraction, transformation and loading techniques in order to connect large data sets from a variety of sources, creates data collection frameworks for structured and unstructured data, develops and maintains infrastructure systems (e.g., data warehouses, data lakes) including data access APIs, and deploy models into production environments integrated with manufacturing systems.
What You'll Be Doing
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Developing End-to-End ML Pipeline design, build, and deploy robust ML models from data ingestion to production deployment, ensuring automation, scalability, and maintainability
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Implement MLOps best practices including CI/CD for ML, monitoring, retraining pipelines, and model governance
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Building experimental prototypes to test different machine learning approaches and validate concepts before full implementation
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Working closely with data scientists, business analysts, and manufacturing SMEs to understand project requirements, interpret results, and communicate insights effectively
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Applying software engineering principles like version control, code review, and modular design to ensure the maintainability and scalability of machine learning systems
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Staying current with AI/ML advancements, particularly in manufacturing and industrial IoT domains
What You Bring
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Demonstrated experience in building production-grade ML solutions with measurable business impact
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3+ years working as a Machine Learning Engineer or equivalent experience
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3+ years experience with big data platforms and Industrial IOT time-series data
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3-5+ years experience with cloud data platforms like AWS, Azure, or GCP to leverage cloud-based data storage and processing capabilities
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3-5+ years experience with both relational (RDBMS) and non-relational (NoSQL) databases
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Ability to collaborate with data scientists, analysts, and other stakeholders to understand their data needs and translate them into technical solutions
What We’ll Bring
During your interview process, our team can fill you in on all the details of our industry-leading benefits and career development opportunities. A few highlights include:
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A work environment built on teamwork, flexibility, and respect
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Professional growth and development programs to help advance your career, as well as tuition reimbursement
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Team Member Vehicle Purchase Discount
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Toyota Team Member Lease Vehicle Program (if applicable)
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Comprehensive health care and wellness plans for your entire family
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Flexible work options based on business needs
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Toyota 401(k) Savings Plan featuring a company match, as well as an annual retirement contribution from Toyota regardless of whether you contribute
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Paid holidays and paid time off
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Referral services related to prenatal services, adoption, childcare, schools and more
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Tax Advantaged Accounts (Health Savings Account, Health Care FSA, Dependent Care FSA)
Belonging at Toyota
Our success begins and ends with our people. We embrace all perspectives and value unique human experiences. Respect for all is our North Star. Toyota is proud to have 10+ different Business Partnering Groups across 100 different North American chapter locations that support team members’ efforts to dream, do and grow without questioning that they belong.
Applicants for our positions are considered without regard to race, ethnicity, national origin, sex, sexual orientation, gender identity or expression, age, disability, religion, military or veteran status, or any other characteristics protected by law.
Have a question, need assistance with your application or do you require any special accommodations? Please send an email to .