Machine Learning Jobs in Cambridge, MA

Lead planning and delivery of complex software programs for Pickle's robotics platform. Coordinate cross-functional teams (software, robotics, firmware, hardware), manage risks and dependencies, run planning and release activities, improve processes and tracking, and drive alignment to deliver production-quality robotic software in a fast-paced startup.

Design, develop, secure, and modernize scalable omnichannel APIs supporting member-facing applications. Improve API security, resiliency, performance, and observability; apply AI-assisted engineering; collaborate with architecture, security, cloud, product, and operations teams; deliver proofs of concept, reusable patterns, and provide Tier 3 production support and incident response.

Design, implement, and scale production-grade data and ML pipelines for risk and payments. Build ETL and feature engineering workflows, productionize models, establish observability and monitoring, participate in reviews and on-call rotations, and mentor junior engineers to ensure reliable, explainable decisioning systems.

Design, build, and operate scalable, reliable ML inference systems, backend services, and data pipelines for health features. Translate research prototypes to production, ensure monitoring/validation within a quality-managed SaMD environment, provide technical leadership, and participate in on-call rotations to maintain uptime and reliability.

Lead global strategy to optimize and modernize financial crime detection across transaction monitoring, customer risk rating, and fraud models. Drive transition from rules-based controls to AI/ML-driven detection, oversee model lifecycle governance, reduce false positives, ensure regulatory defensibility, and partner with Compliance, Technology, Data, Operations, and vendors to deliver measurable risk and operational improvements.

Graduate-level software engineering intern working in Human-Centered AI. Interns build prototypes with small teams using Python and techniques in machine learning, probabilistic modeling, NLP, cybersecurity, and data analytics. Responsibilities include designing, programming, documenting complex software and rapidly learning new tools while collaborating on project-oriented research.

Develop and maintain geometry processing, simulation, and rendering algorithms; build services to read/process 2D/3D engineering data; curate large datasets; implement ML post-training workflows; and contribute to domain-specific languages for engineering.

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

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

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.

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.

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.

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.

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

Lead enterprise-level strategy and delivery for building design, engineering, data readiness, and AI adoption. Define customer success plans, run workshops, shape consulting offerings, mentor staff, drive change management, and ensure high-quality project delivery and measurable customer value.

Lead development and validation of multimodal computational biomarkers and predictive models by integrating radiology imaging with clinical, molecular, and real‑world data. Design end-to-end ML pipelines, apply deep learning, foundation models, and statistical learning to support patient stratification, endpoint prediction, and translational decision-making. Collaborate with clinicians and scientists, publish results, and ensure work meets governance and quality standards.

Lead development and deployment of advanced data analytics, multivariate and machine learning models, and digital twin initiatives to characterize and improve pharmaceutical manufacturing processes. Collaborate across teams and partners, author technical documentation, support troubleshooting and quality investigations, and drive process monitoring, control strategies, and continuous improvement under cGMP.

The Staff Machine Learning Engineer will design and build scalable ML systems for health insights, collaborating with cross-functional teams to ensure compliance and quality in production-ready services.

The role involves designing and operating AI systems, building data pipelines, fine-tuning models, and mentoring team members while collaborating with product and data science teams.

Lead WHOOP's cloud-based core algorithm teams to develop, validate, and productionize models for sleep, recovery, and training. Drive technical vision, cross-functional alignment with Sensor Intelligence and Hardware, improve ML lifecycle practices (experiment tracking, deployment, monitoring), and manage and grow applied ML scientists and engineers to deliver better member experiences.

Lead full-stack development for an AWS-based product: design and implement backend, data, and web UI; integrate external APIs and AI/ML features; collaborate cross-functionally; improve architecture and engineering practices; mentor teammates and deliver high-quality, production-ready code.

Design and implement pixel-perfect, high-performance web applications from wireframes to production. Collaborate with designers, PMs, and engineers, iterate on architecture and best practices, explore AI/ML integrations, and contribute to a collaborative engineering culture.