Machine Learning Jobs in Cambridge, MA

As a Solution Architect, you will design and architect modern IT systems for healthcare, collaborating with product owners and leading technical discussions to improve efficiency and service delivery.

Lead the Oncology Data Science team in developing data-driven solutions for low molecular weight drug development, leveraging AI and machine learning. Collaborate with stakeholders to execute data science strategies and ensure adherence to best practices in analytics.

Lead design and implementation of LLM observability features: prototype and scale product capabilities for tracing, evaluating, and debugging generative AI systems. Work cross-functionally to influence architecture, mentor engineers, prioritize customer pain points, and drive product and engineering decisions for reliable, high-performance AI observability.

The role involves designing and implementing advanced analytics solutions for healthcare payers, analyzing complex problems, mentoring juniors, and building client relationships.

Evaluate and create AI-generated content in German. Review writing for factuality, completeness, and grammar while producing original content.

Lead the development of machine learning algorithms focusing on perception for autonomous driving, collaborating across teams and mentoring ML developers.

The Product Owner will lead the development of AI/ML-driven digital products for molecular modeling, enhancing scientific workflows and driving product adoption through agile cross-functional team leadership.

Embed with domain teams to prototype, build, and productionize data and AI applications on Palantir Foundry. Design data pipelines, ontologies, and user-facing workflows; ensure data quality, access controls, monitoring, and reuse. Lead discovery to delivery, collaborate with product and platform teams, and mentor peers to drive adoption and durable operational solutions.

Lead ML engineer responsible for designing, building, deploying, and monitoring production ML systems at scale. Collaborate with product and data science teams, develop ML architectures and data pipelines, apply CI/CD and cloud-based MLOps, retrain and govern models, and ensure performance, reliability, and responsible/explainable AI practices.

Lead design, build, and productionize scalable ML models and pipelines. Collaborate with product and data science teams, implement cloud-based architectures, ensure CI/CD, monitoring, model governance, and responsible AI practices.

The Senior Professional Services Solutions Architect will drive sales and delivery of Snowflake services, acting as a trusted advisor while collaborating with customers to solve their data challenges.

The Research Engineer/Scientist will advance decision-making in critical industries using optimization and machine learning, collaborating with product managers and engineers.

The Quantitative Analyst will develop stock selection models, enhance research infrastructure, conduct statistical analysis, and collaborate with investment teams to provide insights.

Senior leader responsible for designing and operating Fidelity's global sanctions program, ensuring OFAC and parallel-regime compliance, driving strategy, governance, technology-enabled screening and analytics, regulatory engagement, and leading a global sanctions team to mitigate enterprise sanctions risk.

Lead and modernize the People Analytics function to deliver timely, actionable workforce insights using advanced analytics, predictive modeling, AI/IA, and self-service tooling. Partner with HR, business, and tech stakeholders to prioritize use cases, ensure data quality and governance, accelerate speed-to-insight, and communicate executive-level narratives. Build and develop a hybrid analytics team, embed analytics into decision-making, and measure business impact.

Lead clinical development for mRNA-based oncology programs: create and manage Clinical Development Plans, design studies and protocols, oversee execution and medical monitoring, drive regulatory interactions and submissions, collaborate cross-functionally and with external partners, mentor clinical staff, and apply innovative/digital approaches to accelerate evidence generation.

Own Roku's audience targeting and activation product surface end-to-end: define audience creation, curation, distribution, and activation across buying paths; set strategy and governance; shape modeled audiences and portability to external platforms; productize new targeting signals; improve self-serve targeting workflows; define success metrics and drive cross-functional execution with engineering, data science, sales, and partners.

Lead the AI Systems & Scale group to design and implement advanced AI systems for drug discovery, overseeing project management and technical leadership.

Lead enterprise Data & AI strategy and act as product and portfolio owner for all Data & AI initiatives. Define strategy, create product-aligned roadmaps, track delivery and value realization, govern portfolio discipline, and produce executive/investor/client communications. Build and lead a small team to ensure roadmap execution, prioritization, and fact-based reporting of outcomes.

Develop and scale machine learning systems for physiological signal processing. Design and train models, ensure compliance, and mentor team members while collaborating with cross-functional teams.

Design, build, and productionize large-scale foundation models and ML systems (transformer architectures, self-supervised learning). Architect and implement training, data pipelines, deployment, monitoring, and CI/CD. Collaborate with cross-functional teams, ensure model governance, reliability, and performance, and apply ML engineering best practices at scale.

Design and develop automated design flows for IC Package and PCB design, incorporating algorithms and machine learning, while collaborating with engineering teams.

The Software Engineer will develop algorithms and code related to AI, robotics, and sensing technologies, impacting key systems at Zoox.

The Senior Machine Learning Engineer leads technical direction for ML systems focused on personalization and ranking, overseeing architecture and implementation while mentoring team members.

The Technical Lead for ML Operations at WHOOP will drive the strategy and execution of ML infrastructure, lead a small team, design scalable systems, and collaborate with multiple stakeholders to enhance the ML platform.