Top AI Research Jobs in Boston, MA

Conduct applied research to design, train, evaluate, and deploy AI foundation models and recommendation/personalization systems. Collaborate with cross-functional teams to build models at scale using PyTorch, cloud infrastructure, and open-source tools. Publish research, deliver platform-level code, and drive long-term research agendas to improve customer experiences.

Lead research on embodied AI for humanoid and high-DOF robots, inventing and validating algorithms across reinforcement and imitation learning, multimodal perception, whole-body control, manipulation, and sim-to-real transfer. Define scientific roadmaps, build evaluation and training pipelines, translate research into real-robot capabilities, publish/patent results, and mentor cross-functional teams to integrate models with hardware for production deployment.

Lead and define a decade-scale research vision spanning perceptual intelligence, sensing, distributed edge orchestration, and trusted systems. Recruit and mentor multidisciplinary teams, launch 12–36 month programs producing deployable models, datasets, APIs, and IP, and drive translation of research into products, platforms, middleware, and strategic pilots. Partner across research, engineering, strategy, and external institutions to ensure scientific quality and long-term enterprise impact.

The Lead Research Scientist develops advanced AI/ML technologies for signals exploitation and system management while leading project teams and collaborating with customers.

Lead Applied AI/ML strategy and development for Internal Medicine Research, translating foundation models, agentic and multimodal AI into reusable, validated capabilities. Define governance, evaluation standards, prioritize high-value use cases, manage external partnerships, and drive adoption across IMRU while ensuring scientific rigor, reproducibility, and human oversight.

Lead MongoDB's strategy to increase LLM and answer-engine visibility by optimizing content, structured data, and community signals. Build and scale an AEO/SEO team, implement technical information architecture (JSON-LD, knowledge graphs, RAG-friendly docs), coordinate UGC/community advocacy, evangelize AI-first content practices, and develop analytics/attribution (Share of Model, citation impact) to drive PLG acquisition.

Manage and coach a team of mentors to ensure delivery outcomes for ~200 AI fellows at scale. Build delivery systems, run operational cadence, lead live instruction when needed, translate field signals into curriculum changes, and partner with strategic partners to close the feedback loop between mentors, fellows, and the curriculum team.

The Director of Statistics leads statistical projects in clinical research, implements innovative methodologies, designs trials, and collaborates with teams to analyze results, ensuring regulatory compliance and contributing to cardiovascular disease treatments.

Lead the development and integration of advanced safety systems for scientific AI applications, building a team and establishing a research strategy.

The AI Scientist will lead the development of biomolecular modeling technologies, focusing on creating and validating AI models for drug design using experimental feedback.