Top Senior Machine Learning Jobs in Boston, MA

Lead WHOOP's strategy for transforming sensor data into real-time intelligence, managing teams, delivering features, and driving technical direction in machine learning and embedded systems.

Develop and scale machine learning systems to enable AI coaching, collaborate across teams for member insights, and contribute to architectural decisions.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

Lead the SDL and Cash Line ML teams, developing innovative machine learning models to improve lending solutions and expand credit access. Collaborate with cross-functional teams to drive product strategy and enhance model performance, while mentoring a team of ML scientists.

The Senior Machine Learning Engineer designs and develops ML systems, collaborates with teams to meet analytical needs, and optimizes large-scale ML solutions while setting monitoring and best practices.

Lead the development of healthcare data products using machine learning. Design models, collaborate with teams, and mentor others in statistical methods.

As a Principal Applied Scientist, you'll define the technical vision for offer optimization and conversion modeling systems, ensuring alignment across teams while overseeing large technical initiatives and contributing to real-world machine learning 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.

Manage a team of ML engineers to build and optimize Affirm's economic decisioning engine using advanced ML techniques. Collaborate across teams, provide technical leadership, and mentor engineers while driving a cohesive long-term ML strategy.

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, 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.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

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.

Lead design, build, deploy, and maintain production ML and AI systems (including LLM inference, RAG, similarity search, observability, and governance). Collaborate cross-functionally to create data pipelines, retrain and monitor models, and apply responsible, explainable AI practices while contributing technical vision and roadmap for AI solutions.

Lead actuarial data scientist to oversee technical pricing models, actuarial systems, and a team of actuarial data scientists. Develop strategic roadmap, establish modeling standards and validation, apply ML/AI to pricing, collaborate with legal/compliance, present insights to executives, and manage projects to deliver high-quality actuarial products.

Lead development and maintenance of AML typologies and analytics to detect and mitigate financial crime. Collaborate with cross-functional teams and FIU, build and deploy machine learning models, perform data transformation/ETL, and produce actionable insights. Provide technical leadership across analytics projects, mentor colleagues, and ensure solutions align with regulatory and enterprise risk frameworks.

The Senior Machine Learning Engineer will design and deploy scalable machine learning models, optimize performance, and lead best practices while collaborating with cross-functional teams.

Design, develop, test, and deliver new features for Red Hat OpenShift AI. Build open-source machine learning and data-science pipeline software, perform full-stack TypeScript/Node.js/React development on OpenShift, run unit and end-to-end tests, participate in code reviews and agile ceremonies, contribute to patents, and engage with the open-source community.

As a Senior Lead Machine Learning Engineer, you'll design and implement machine learning applications, lead teams, and optimize systems and data pipelines while collaborating in an Agile environment.

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.

Lead development of motion planning and prediction ML models for Level 4 autonomous vehicles. Design and productionize behavior models using deep learning, generative AI, and reinforcement learning. Deploy solutions to vehicle fleets, collaborate with perception, simulation, data platform and integration teams, and report progress to leadership.

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.