5,612 Machine Learning Architect jobs in the United States

• Lead and Architect
• Confidently drive every stage of the ML software development lifecycle, from initial concept to full-scale production deployment
• Lead workshops to gather technical and business requirements, translating customer pain points into actionable AI and data science strategies
• Advise internal and external stakeholders on trends in Data & AI, influencing both technical direction and strategic initiatives to scale the company's ML market share
• Architect and implement robust, scalable, and data-driven machine learning applications within Azure, balancing business value with technical innovation
• Produce thought leadership through GitHub contributions, blog posts, or technical talks on LinkedIn or YouTube to elevate both personal and company profiles
• Build
• Build end-to-end machine learning pipelines across supervised, unsupervised, and deep learning paradigms, with strengths in inferential statistics, time series, computer vision, or LLMs.
• Engineer ML solutions that integrate seamlessly with Azure cloud infrastructure, ensuring performance, scalability, and maintainability.
• Utilize state-of-the-art DevOps and MLOps practices (CI/CD pipelines, containerization, and automated governance) to build production-ready systems.
• Collaborate and Persuade
• Serve as the bridge between sales, leadership, and customers, identifying client pain points and translating them into tailored, profitable ML solutions
• Communicate complex technical architectures and ML solutions to diverse audiences, simplifying concepts for non-technical stakeholders
• Navigate ambiguity in customer goals and evolving technical landscapes, while driving towards clear, measurable outcomes
• Mentor and Cultivate
• Be a mentor and role model for team members, fostering a high-performance MLE culture
• Foster psychological safety where team members are encouraged to challenge the status quo, propose new approaches, and fail productively
• Help grow and shape a technical team capable of delivering high-impact ML projects at scale

• Technical Expertise:
• Languages/Frameworks : Python, working knowledge of Scala, Java, or PySpark. Pandas, numpy, sklearn, LangChain
• Azure : Deep knowledge of Azure's ecosystem including Azure ML, Data Factory, Databricks, Data Lake Storage, Cosmos DB, and Azure SQL DB.
• System Design : Expertise in designing Azure architecture following Domain-Driven Design principles
• AI & ML Skills: Proficiency in supervised, unsupervised, and deep learning models, including hands-on experience with LLM architectures, time series forecasting, and computer vision solutions
• MLOps & DevOps: Strong understanding of MLOps pipelines and MLFlow, CI/CD automation with Azure DevOps or GitHub Actions, and containerization technologies like Docker and Kubernetes
• Tools : Proficient in GitHub, PowerShell, Azure CLI, and infrastructure-as-code tools such as ARM templates or Terraform
• Soft Skills & Leadership:
• Proven experience leading high-performance teams in a fast-paced, customer-centric environment
• Strong ability to communicate technical concepts to non-technical stakeholders, and to translate business objectives into scalable ML systems
• Ability to mentor and grow teams, setting high standards for both technical quality and engineering discipline
• Experience:
• 10+ years of experience in system design, ML/AI architecture, and enterprise data infrastructure
• Demonstrable experience building ML applications in industries such as Manufacturing, Retail, Financial Services, and Healthcare
• Hands-on experience with LLM architectures, including Retrieval-Augmented Generation (RAG), single and multi-agent systems, and custom router solutions
• Experience with API development frameworks (FastAPI, Django REST framework) to support scalable data services

• Microsoft MVP.
• Strong software engineering experience.
• Experience in professional services organizations.
• Demonstrable thought leadership through an active GitHub, blog posts, or publications.
• LLM experience: RAG, single and multi-agent, custom routers.
• Azure Fabric implementation.
• Scala, Java, Terraform.

About this role We are looking for a world-class ML leader to architect and own our AI roadmap. This is a foundational role that will work closely with the founders to define the technical trajectory across our platform, including code generation, reinforcement learning, layout optimization etc.

You'll lead a growing ML team and work cross-functionally to turn cutting-edge research into usable tools for chip engineers. You should bring deep expertise in ML for chip design, as well as leadership experience in high-performance engineering teams.

Responsibilities

• Contribute to building the ML roadmap and research strategy for Architect across RTL and PD domains.
• Architect and deploy novel agent-based systems, including fine-tuning models for RTL Code generation, physical design tasks automation and hardware problem reasoning.
• Lead, mentor, and scale a team of top-tier ML engineers. Guide research direction, implementation standards, and modeling infrastructure.
• Interface with hardware engineers to identify bottlenecks in chip design pipelines that ML can solve.
• Stay ahead of state-of-the-art techniques in ML4EDA, agent orchestration, and model compression/deployment.

Tiger Analytics is looking for an experienced Principal Data Scientist to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. You will be responsible for:

• Highly experienced Machine Learning Architect with a proven track record of designing and delivering end-to-end ML solutions across diverse business domains. The ideal candidate will have over 10 years of experience in data science, machine learning, and MLOps, and a deep understanding of scalable system design, model lifecycle management, and production-grade deployment pipelines.
• This is a strategic and hands-on role, involving collaboration with data scientists, engineers, product teams, and business stakeholders to architect solutions that are robust, scalable, and aligned with business goals
• You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

• Design and define system architecture for ML and AI-driven solutions across multiple business verticals.
• Lead ML system design discussions and make high-level design choices for model serving, data pipelines, and MLOps frameworks.
• Architect scalable and secure cloud-native platforms for ML model training, validation, deployment, and monitoring (AWS/GCP/Azure).
• Build reusable components and reference architectures for various stages of the ML lifecycle.
• Define and enforce best practices in model versioning, CI/CD for ML, testing, and rollback strategies
• Deploy and manage machine learning & data pipelines in production environments.
• Work on containerization and orchestration solutions for model deployment.
• Participate in fast iteration cycles, adapting to evolving project requirements.
• Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications.
• Collaborate with Data scientists, software engineers, data engineers, and other stakeholders to develop and implement best practices for MLOps, including CI/CD pipelines, version control, model versioning, monitoring, alerting and automated model deployment.
• Ability to work with a global team, playing a key role in communicating problem context to the remote teams
• Excellent communication and teamwork skills

• Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field.
• Typically requires 10+ years of hands-on work experience developing and applying advanced analytics solutions in a corporate environment with at least 4 years of experience programming with Python.
• At least 7 years of experience productionizing, monitoring, and maintaining models
• Strong programming skills in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Deep experience with MLOps tools such as MLflow, Kubeflow, Airflow, SageMaker, or Vertex AI.
• Hands-on experience designing ML systems using cloud platforms like AWS, Azure, or GCP.
• Strong understanding of data engineering, APIs, CI/CD pipelines, and model observability.
• Excellent communication and stakeholder management skills.

Full-time or part-time: Full-time

Job title: Machine Learning Architect

Job Location: 2700 Sand Hill Road, Menlo Park, CA 94025

Job Description:

Lead the design and implementation of state-of-the-art machine learning models and algorithms to solve complex business problems. Utilize various techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning, to extract insights from large datasets. Conduct exploratory data analysis to uncover patterns, trends, and relationships in the data. Identify relevant features and variables for model development and feature engineering. Develop data preprocessing, cleansing, and augmentation strategies to improve model performance. Ensure that machine learning models are transparent and interpretable by utilizing explainable AI techniques. Develop methods to interpret model predictions and comprehend model behavior, especially in high-stakes or regulated domains. Lead the development of backend services and infrastructure to support machine learning applications across various platforms and surfaces, ensuring seamless integration with existing systems. Design GPU optimized model pipelines to efficiently process diverse data modalities, including images, vectors, and 3D assets. Design internal AI platforms and frameworks for model inference and deployment and develop highly scalable and resilient systems to efficiently handle large-scale machine learning workloads. Collaborate closely with cross-functional teams of data scientists, software engineers, and product managers to employ innovative architectures and cutting-edge techniques to develop optimized solutions for business problems and offer technical leadership to ensure alignment with organizational goals.

Minimum Education & Experience Requirements:

Master's degree, or foreign educational equivalent, in Computer Science, Mathematics, Physics, Applied Science, or a related STEM field, plus 2 years of post-baccalaureate experience in job offered or any Machine Learning/engineering related job titles.

Applicants must have 2 years of experience in the following: (1) data analytics, developing Machine Learning (ML) algorithms, optimization methods, and Deep Learning (DL) and Neural network libraries to optimize neural networks and train and evaluate different models; (2) Natural Language Processing, Computer Vision Technologies, Reinforcement learning, and semi-supervised learning; (3) Software development and programming skills with databases and ML frameworks; (4) data science development tools and languages including R, Python, Java, TensorFlow, PyTorch, Flask; (5) developing technologies for inference, predictive modeling, general-purpose data-driven modeling, and optimization of systems; (6) Generative AI technologies and Foundational Models; and (7) processing multivariate data sets collected from equipment operations, manufacturing tests, and diagnostic routines.

Compensation for role: $200,304- $231,600/year

Company policy is to provide every individual a fair and equal opportunity to seek employment and advancement at the Company without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, citizenship, genetic information, veteran or military status, disability, creed, ancestry, pregnancy (including pregnancy, childbirth and related medical conditions), marital status or any factors protected by federal, state, or local laws. We are an "Equal Opportunity Employer". For more information please, refer to the latest version of "Know Your Rights" poster and the "Pay Transparency Nondiscrimination Poster" located here: The Company is a VEVRAA Federal Contractor - priority referral Protected Veterans requested.

• 10+ years of related work experience,
• Proven experience (8+ years) in AI/Client roles with a strong track record of successful AI project implementations.
• Developed and created solution for on large AI/Client models for enterprise
• Strong leadership and communication skills with the ability to influence and inspire others.
• Passion for innovation and a strong desire to drive AI adoption and transformation.
• Proficient in programming languages such as Python, R, or Java.

• Design machine learning solutions and execute machine learning projects end to end from proof-of-concept stage to deployment in production using cloud native technologies and state of the art machine learning models.
• Be technically focused but work directly with the business representatives/customers to understand the requirements driving the need for a solution to be developed.
• Be responsible for all phases of the project from problem definition, data annotation, model development, model deployment to end user documentation/training.
• Design the architecture of ML solutions on cloud platforms (AWS, Azure, GCP) including MLOPs.
• Stay abreast of the latest developments. Read the latest published machine learning research and adapt the models to solve customer's problems.
• Establish credibility by demonstrating technical excellence and delivering value through solutions you build. Develop strong relationships with our customers.

• Masters with 10+ years of experience or PhD with 6+ years of experience in Machine Learning, Natural Language Processing (NLP) and Deep Learning.
• Minimum 5+ years of experience architecting and building Machine Learning solutions.
• Minimum 5+ years of experience with cloud platforms (AWS, GCP, Azure).
• Experience building ML models and strong knowledge of ML techniques is required.
• Experience with hugging face, TensorFlow/pytorch, transformer architectures, prompt engineering, agentic systems, LLMs.
• Strong coding experience in Python and architectural patterns like microservices.
• Solid understanding of agile methodologies and experience in planning machine learning projects from inception to production deployment.
• Strong problem-solving skills and the ability to lead a team on "what's next" when encountering a technical issue in a machine learning project.
• Excellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.

• As per business requirements

• Design machine learning solutions and execute machine learning projects end to end from proof-of-concept stage to deployment in production using cloud native technologies and state of the art machine learning models.
• Be technically focused but work directly with the business representatives/customers to understand the requirements driving the need for a solution to be developed.
• Be responsible for all phases of the project from problem definition, data annotation, model development, model deployment to end user documentation/training.
• Design the architecture of ML solutions on cloud platforms (AWS, Azure, GCP) including MLOPs.
• Stay abreast of the latest developments. Read the latest published machine learning research and adapt the models to solve customer's problems.
• Establish credibility by demonstrating technical excellence and delivering value through solutions you build. Develop strong relationships with our customers.

• Masters with 10+ years of experience or PhD with 6+ years of experience in Machine Learning, Natural Language Processing (NLP) and Deep Learning.
• Minimum 5+ years of experience architecting and building Machine Learning solutions.
• Minimum 5+ years of experience with cloud platforms (AWS, GCP, Azure).
• Experience building ML models and strong knowledge of ML techniques is required.
• Experience with hugging face, TensorFlow/pytorch, transformer architectures, prompt engineering, agentic systems, LLMs.
• Strong coding experience in Python and architectural patterns like microservices.
• Solid understanding of agile methodologies and experience in planning machine learning projects from inception to production deployment.
• Strong problem-solving skills and the ability to lead a team on "what's next" when encountering a technical issue in a machine learning project.
• Excellent communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.

• As per business requirements