Machine Learning Jobs in Cambridge, MA

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.

This role focuses on conducting research in equity markets using ML and NLP for alpha generation. You'll collaborate with global teams to develop models and translate innovations into strategies.

Lead and mentor ML engineers and data scientists, overseeing ML strategy and development of scalable models for healthcare applications.

Lead the design and implementation of a robust data architecture for clinical datasets, focusing on real-time sensor data processing and API integrations with wearables.

The Director of Product Management will lead incident management product strategy, integrate analytics into workflows, manage a small team, and ensure product alignment with user needs in emergency management contexts.

Lead and improve machine learning systems for safety in personalization, develop backend services, and partner across teams to address safety challenges.

Develop advanced learning algorithms for dexterous robots, create simulations, and manage data collection and evaluation frameworks.

As a Senior Sales Engineer at H2O.ai, you'll lead pre-sales efforts by leveraging technical expertise in AI to design solutions for enterprise customers, drive ROI demonstrations, and guide AI adoption. You'll collaborate with multiple teams and influence product roadmaps while showcasing hands-on skill with LLMs and cloud-based deployments.

Build and scale core components of an end-to-end proteomics software stack (LIMS, data pipelines, web portal). Design agentic backends and AI-augmented tooling, develop analysis algorithms and lab integrations, deploy cloud IaC and CI/CD, write tests and monitoring, and collaborate with R&D, operations, and customers to productionize tools for high-throughput proteomics.

Lead digital marketing measurement and data science, analyze digital data, develop statistical models, and collaborate with marketing teams for optimization and insights.

Lead the development of robot learning models, design simulation environments, optimize policies for real-world robots, and contribute to data lifecycle management.

Develop core AI technologies for robotics, focusing on advanced learning algorithms, simulations, data collection, and staying updated on ML and robotics advancements.

Manage third parties and risks, ensure compliance and support procurement. Lead risk assessments, document AI-related risks, and enhance governance frameworks.

Lead integration and analysis of multi-modal omics (spatial transcriptomics, proteomics, imaging, sequencing) using statistical, machine learning, and AI methods to support oncology target discovery. Build scalable, reproducible workflows on HPC, partner with cross-functional teams, evaluate emerging technologies, ensure data quality, and communicate findings to technical and non-technical stakeholders.

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.

As a Robotics ML Research Engineer, you will develop algorithms for robot manipulation, lead software infrastructure, and innovate in robotics learning research.

The Computational Research Scientist will focus on computational drug discovery and antibody functional screening, leading research projects and contributing to publications while supervising lab personnel.

Seeking a Research Manager to lead teams in AI and robotics, defining research strategies and overseeing project deployments from concept to execution.

As an ML Research Scientist, you will develop AI systems for multimodal data extraction and advance scientific knowledge structuring across domains.

The role involves developing synthesis-aware virtual screening workflows for small-molecule drug discovery, integrating various modeling and design strategies.

Lead the company's finance function—oversee accounting, GAAP financial reporting, audits, budgeting, cash management, R&D expense tracking, and compliance. Drive long-range planning, scenario modeling, fundraising support, implementation of scalable finance systems, manage external vendors, and deploy AI/automation to improve finance operations.

Lead end-to-end strategy and execution for a B2B SaaS data platform, identifying high-impact opportunities, driving AI/data-enabled features, managing roadmaps, leading discovery, and coordinating cross-functional GTM and delivery to achieve commercial outcomes.

The Digital Engineering Data Solutions Architect will develop data architectures, support system lifecycle management, and collaborate on innovative solutions in national security projects.

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.

The AI Data Specialist builds and maintains data pipelines, models, and integrations for AI systems, working closely with clients to ensure data quality and effective communication. They manage end-to-end data delivery for multiple projects in a fast-paced environment, translating complex problems into clear solutions.