Top Machine Learning Jobs in Boston, MA

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

The ML Data Engineer develops and maintains machine learning pipelines and systems, collaborating with teams to optimize manufacturing processes through data-driven insights and predictive models.

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

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.

Develop AI/ML algorithms for signals exploitation, perform modeling and simulations, and engage in project teams for innovative solutions.

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

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 Machine Learning Engineer, you'll build and deploy AI/ML models, design workflows, and drive product development in a startup focused on the collectibles industry.

As a Principal Engineer specializing in AI/ML, you'll define the technology strategy, lead cross-functional initiatives, and develop innovative ML solutions while influencing technical decisions across the organization.

The Principal AI/ML Software Engineer drives ML technology strategy and innovation, develops solutions for complex problems, and leads cross-functional initiatives while shaping the technical vision and architectural frameworks for AI/ML.

The Senior Machine Learning Engineer will design, build, and deploy AI agents at scale, enhancing Dropbox Dash's search and organization features. Requires extensive ML experience and proficiency in Python and ML libraries.

The role involves building predictive models for blockchain performance and user behavior, implementing solutions, and owning production prediction pipelines.

The role entails managing an Agile team focused on design, development, and implementation of scalable machine learning applications while ensuring architecture performance and model 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.

Lead the design and implementation of advanced ML systems at Airbnb, mentoring engineers and shaping concepts into impactful products.

As an Applied Scientist, you will design and implement machine learning models, develop personalized systems, and enhance decision-making through AI technology to improve user experience and business operations.

As a Staff ML Research Engineer, you will develop and optimize ML algorithms for drug discovery, transitioning high-impact prototypes into robust products and managing software development across the lifecycle.

The Senior Lead Machine Learning Engineer will design, develop, and implement machine learning systems, collaborating with teams to solve business problems using machine learning applications.

Lead development of machine learning models for drug discovery, integrating ML with molecular modeling to enhance molecular design and optimization approaches.

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

Lead the design and delivery of large-scale machine learning systems, mentoring engineers while driving technical strategy and collaboration across teams in AEC solutions.

Lead machine learning projects, collaborate with business partners, and manage data processes from research to production to drive business impact.

Lead a team of Machine Learning engineers, drive technical direction, oversee large-scale ML systems and improve user experience for over 500M users.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.