Top Machine Learning Jobs in Boston, MA

As an AI Product Specialist, you'll drive market expansion and customer engagement by defining strategies for AI product growth, conducting market analyses, and supporting sales teams. You'll leverage AI expertise and guide product development and competitive positioning while collaborating across teams to enhance Kensho's AI solutions.

The Senior Researcher will develop and implement algorithmic capabilities in autonomy, focusing on AI/ML applications to solve national security challenges, while collaborating across multidisciplinary teams and engaging with customers.

In this role, you will develop AI foundation models, perform applied research, collaborate with cross-functional teams, and leverage advanced technologies to enhance customer experiences in banking.

Lead Data Scientist responsible for guiding teams in data analysis, algorithm development, and AI application to address national security challenges. Engage stakeholders and oversee algorithm testing and evaluation.

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

Leads AI strategy and technical direction for applied AI in Inflammation & Immunology, overseeing portfolio development, partnerships, and governance standards to improve scientific decision-making.

The Applied AI Workflow Scientist, Sr. Manager drives the application of AI and LLMs in scientific workflows, collaborating with various stakeholders to improve operational efficiency in Immunology and Inflammation.

Lead data science projects to optimize drug development, develop AI models for clinical trials, and collaborate with teams on biomedical workflows.

As a Data Scientist, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

Manage AI engineering teams and client relationships, drive project deliverables, mentor staff, and uphold quality standards while leveraging advanced technologies.

The role involves managing client needs through technology solutions, mentoring team members, analyzing complex problems, and using AI/GenAI to enhance productivity and client relationships.

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

Lead the AI strategy and vision for Avigilon products, defining and architecting AI-enabled user experiences, and collaborating across teams to drive consistency and performance in AI capabilities.

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

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.

Lead data science projects to advance drug development, implementing models for patient selection and clinical trial optimization, and collaborating with cross-functional teams.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

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.

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.

The Machine Learning Engineer will design, build, and maintain production machine learning systems, focusing on scalability, reliability, and integration with existing products. Responsibilities include developing ML pipelines, establishing ML Ops best practices, and collaborating on product capabilities.

Lead development of a greenfield data product by partnering with customers and product teams to build analytics and models (simulation, Bayesian networks, optimization, ML). Maintain existing analytics, improve predictive churn models, and translate customer needs into production-grade SQL/dbt pipelines, dashboards, and data-driven product features.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

As a Senior AI Engineer, you'll design and implement AI-driven solutions, focusing on full-stack development and production-grade applications while mentoring junior team members.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.