Machine Learning Jobs in Cambridge, MA

Lead and manage consulting engagements delivering power market analysis, price forecasts, asset valuations, transaction support, and strategic advisory. Oversee modeling (PROMOD, PSLF, PLEXOS, Aurora), mentor staff, manage client relationships, drive business development, publish thought leadership, and contribute to proprietary forecasting and analytical tools across U.S. power markets and technologies including renewables, storage, transmission, and large loads.

Sell Loka's GenAI and cloud solutions to biotech and pharma clients. Manage full sales cycle with support, build and maintain client relationships through meetings and events, understand clients' technical and business needs, conduct market research, manage sales initiatives, and maintain life sciences industry knowledge.

As a Research Scientist, you will develop innovative machine learning techniques for clinical applications, design large language models, and collaborate with engineering teams while advancing NLP research.

Perform quantitative research and development of ESG factors, models, and ratings; build alpha generation, portfolio construction, and risk analytics; procure and transform data; run optimizations and backtests; apply ML/NLP/LLMs to extract investment insights; program in Python, R, MATLAB, SQL, and VBA and use FactSet/Bloomberg.

Drive business development in biotech and biopharma, managing strategic accounts and closing enterprise deals. Partner with cross-functional teams for project execution and provide customer insights to shape product direction.

Lead the development of pricing intelligence and reconciliation systems for travel services, focusing on AI-driven insights and cross-functional execution.

Serve as an AI-fluent implementation consultant for Veeva Vault Safety: advise on AI strategy, design validation and governance frameworks, build monitoring dashboards, run workshops, lead gap analyses and configurations, train customers, and ensure GxP/CSV compliance throughout implementations.

The Machine Learning Scientist will develop AI frameworks for predictive modeling in oncology, collaborating with teams to enhance drug R&D efforts through advanced machine learning techniques and multimodal data integration.

Conduct quantitative research to design and validate trading models, alpha signals, and analytics; apply statistical and ML methods to large financial datasets; develop research code and AI tools (Python, Matlab, SQL); collaborate with traders, SSA researchers, and academics to translate findings into scalable trading indicators and internal/client materials.

Audit and improve human and model-generated data outputs for accuracy, consistency, and policy compliance. Provide actionable feedback, clarify evolving guidelines, support annotators, coach new team members, monitor workflows and blockers, identify recurring issues and edge cases, participate in calibration discussions, and document findings to improve team performance and quality at scale.

Provides strategic and technical statistical leadership across the pharmaceutical CMC lifecycle, including process and analytical development, manufacturing, validation, stability, quality control, and regulatory submissions. Establishes a CMC Statistics Center of Excellence, defines governance and best practices, applies DOE, SPC, regression, multivariate, predictive, and advanced analytics methods, and supports investigations and regulatory interactions. Partners across development, manufacturing, quality, regulatory, and digital organizations while building statistical capabilities and training programs.

Leads the design, deployment, operation, and continuous improvement of secure enterprise AI platforms across Azure, AWS, and private clouds. Manages cloud services, Kubernetes, databases, LLM and AI/ML platforms, automation, infrastructure as code, CI/CD, monitoring, identity and access, incident response, resiliency, disaster recovery, governance, and compliance. Partners with engineering, security, data, risk, architecture, and business teams to deliver production-ready and responsible AI solutions.

Develop and implement quantum error correction protocols and decoding algorithms, collaborating with academic and industry partners on a Rydberg atom quantum computer.

Develop and implement quantum error correction protocols and decoding algorithms using machine learning methods on unique hardware aimed at fault-tolerant quantum logic execution.

Lead research at Galois by developing externally funded programs in Formal Methods, collaborating with teams, mentoring staff, and engaging with clients.

Lead a small wet-lab team to translate human genetic insights into target discovery and validation. Design and execute experiments to functionally characterize rare variants, integrate biobank and clinical genetic data, manage resources across projects, drive genotype-to-phenotype strategy, represent genetics in cross-functional governance, and build internal and external partnerships to inform therapeutic target prioritization.

The Senior Machine Learning Engineer will develop and maintain algorithms/services for multi-agent AI, deliver cloud-native architecture, and optimize ML models for performance.

Architect and engineer core software for robotic and machine learning systems, contribute to project planning, and collaborate within teams.

The role involves developing software for robots to enhance capabilities in vision, motion, and control, focusing on complex problem-solving.

Lead client-facing finance transformation engagements to optimize finance functions through operating model design, process improvement, automation and AI. Manage project teams and client relationships, deliver high-quality recommendations and tools, identify value-creation opportunities across G&A, support business development, and coach junior staff.

Generate:Biomedicines invites interested candidates to submit resumes for potential future openings in machine learning and biological engineering.

The Head of Data Science & AI Engineering leads Ipsen's technical strategy in advanced analytics and AI, overseeing data products, mentoring teams, and ensuring compliance in a dynamic biopharmaceutical environment.

Lead Vertex's enterprise AI governance program: define strategy, Responsible AI framework, policies, risk management, and the AI governance platform. Partner with Legal, Privacy, Security, Quality, and business teams to ensure compliant, auditable, and scalable AI adoption across the company.

Drive discovery and delivery for Manifest, translating operational needs into product requirements, roadmaps, and shipped AI-enabled capabilities. Collaborate with engineering, design, and customers, support deployments, track usage and impact, and ensure adoption in mission-critical defense logistics environments.

Advise product, AI, employment, and operational teams on global privacy, data protection, and ethical AI compliance. Lead privacy impact assessments, data subject access requests, data processing agreements, cross-border transfer mechanisms, and third-party reviews. Support incident response and remediation, develop scalable privacy and AI processes, and apply AI tools to improve legal operations. The role requires practical judgment, collaboration, and expertise with global privacy regulations in a highly regulated technology environment.