Top Machine Learning Engineer Jobs in Boston, MA

Design, implement, test, deploy, and iterate machine learning and optimization models and systems. Collaborate with data scientists, engineers, and product managers to scale ML solutions, research new techniques, and improve data quality and predictive applications.

Design and implement cloud architectures for machine learning workflows. Automate cloud resource management using IaC tools, and manage containerization for scaling applications. Requires a Master's or PhD with specific experience in relevant technologies.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

The Staff Machine Learning Engineer will design and build scalable ML systems for health insights, collaborating with cross-functional teams to ensure compliance and quality in production-ready services.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Lead the machine learning strategy, design scalable ML systems, drive MLOps, mentor engineers, and comply with AI governance.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Build and deploy AI/ML models for various asset categories, design workflows, and quickly prototype solutions using customer data.

Lead ML engineer responsible for designing, building, deploying, and monitoring production ML systems at scale. Collaborate with product and data science teams, develop ML architectures and data pipelines, apply CI/CD and cloud-based MLOps, retrain and govern models, and ensure performance, reliability, and responsible/explainable AI practices.

Lead design, build, and productionize scalable ML models and pipelines. Collaborate with product and data science teams, implement cloud-based architectures, ensure CI/CD, monitoring, model governance, and responsible AI practices.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

Develop and scale machine learning systems for physiological signal processing. Design and train models, ensure compliance, and mentor team members while collaborating with cross-functional teams.

Design and deploy production-grade ML systems, integrate models into software pipelines, and develop features leveraging ML for optimization and prediction problems.

Design, build, and productionize large-scale foundation models and ML systems (transformer architectures, self-supervised learning). Architect and implement training, data pipelines, deployment, monitoring, and CI/CD. Collaborate with cross-functional teams, ensure model governance, reliability, and performance, and apply ML engineering best practices at scale.

As a Senior Machine Learning Engineer in the Health team, you'll design and productionize ML systems for personalized health metrics, collaborating with data scientists and engineers to optimize performance and ensure service reliability.

Design, build, and deploy machine learning and AI models into production. Develop tools, APIs, and full-stack internal tooling (VueJS, Java, Postgres). Maintain production Python services with testing, observability, and monitoring (DataDog, Sentry, Kibana). Collaborate with Data Science on model training, deployment, monitoring, and refactor code for performance and maintainability.

As an MLOps Engineer at Kensho, you will develop tools and processes for ML workflows, assist ML engineers, and drive adoption of best practices across teams.

Lead development, deployment, and maintenance of production ML and AI systems (including LLM inference, RAG, similarity search, observability, and governance). Collaborate cross-functionally to build data pipelines, fine-tune foundation models, apply responsible AI practices, and contribute technical vision for scalable, high-performance AI infrastructure in risk management.