Machine Learning Jobs in Cambridge, MA

Own end-to-end product design for an LLM-powered healthcare platform. Design and prototype intuitive, accessible interfaces for clinical users, collaborate with engineering, product, and clinical teams, and shape design culture and processes as an early-design hire.

Seeking a Senior AI Engineer to develop AI solutions, oversee project delivery, and collaborate on system architecture. Requires 5+ years with Python and AI technologies.

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.

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

The role involves leading product strategy and execution, managing product backlogs, and collaborating with cross-functional teams to deliver AI-driven solutions.

As an AI Product Specialist at Kensho, you will drive market expansion, manage customer engagement, and leverage AI product strategies while collaborating across teams to ensure effective go-to-market execution for AI solutions.

As an MLOps Engineer at Kensho, you will develop tools and processes for ML workflows, assist ML engineers, and drive adoption of best practices across teams.

Own and set technical direction for the Everand backend, building scalable, reliable systems for discoverability, personalization, and core consumption journeys. Drive architecture, platform health (CI/CD, staging, DBs, queues, cost, observability), mentor engineers, lead cross-team planning, modernize legacy systems, and partner with product, design, analytics, web/mobile, and ML to support experimentation and telemetry-driven decisions.

Lead statistical activities for clinical trials from protocol design through reporting. Provide statistical oversight, collaborate with cross-functional teams and CROs, apply SAS/R (and ML) for analyses, automate processes, and mentor junior statisticians.

Implement and maintain record-matching and text-analytics components, translate linguistic theory into production features, optimize search internals (Elasticsearch), collaborate in agile sprints, and help design scalable APIs and architectures to improve record-matching quality and reliability.

Develop computational methods to process and interpret nanopore and electrophysiology data. Build event-detection, classification, and fingerprinting pipelines; create quantitative models linking signals to molecular identity; collaborate with experimental teams and ML, protein, and signal-processing groups; establish benchmarking and uncertainty quantification practices.

Lead and build a computational sciences team to develop algorithms, ML models, and scalable data infrastructure for nanopore-based protein reading. Partner with experimental teams to design analyses, implement ML pipelines, manage cloud infrastructure, establish reproducible data practices, protect IP, and communicate progress to leadership and external partners.

Design and implement scalable Snowflake-based data architectures on cloud (Azure/AWS). Build and optimize ETL using SnowSQL and Spark, tune performance, migrate data systems, document designs, collaborate with stakeholders, and mentor engineers while incorporating agentic AI into the data engineering SDLC.

Develop, deploy, and operate distributed research software and transition prototypes to production using OpenShift/OpenStack and other open-source tools. Collaborate with researchers to design, train, and optimize AI/ML models (including LLMs), contribute to open-source projects, and support student-focused activities like hackathons and mentoring.

Lead design and execution of preclinical and translational biomarker strategies for DAx programs. Serve as biomarker representative on project teams, define hypotheses and evidence requirements, develop integrated assay and analysis plans, generate translational evidence, and coordinate cross-functional and external partnerships to support target validation through early clinical readiness.

Provide scientific and operational leadership for imaging strategies (PET/SPECT) across oncology, neuroscience, and cardio/renal/metabolic programs. Design and implement imaging biomarkers, partner with clinical teams and CROs, evaluate novel imaging and AI-enabled analytics, and ensure quality multisite trial execution to inform drug development decisions.

Lead the Advanced Development software workstream for ICE Imaging: define technical strategy, develop and validate ultrasound imaging, computer vision and AI algorithms, mentor engineers, manage cross-functional alignment, and transition research prototypes into regulated commercial medical products.

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.

Lead development, deployment, and maintenance of production ML and AI systems (including LLM inference, RAG, similarity search, observability, and governance). Collaborate cross-functionally to build data pipelines, fine-tune foundation models, apply responsible AI practices, and contribute technical vision for scalable, high-performance AI infrastructure in risk management.

Lead development, validation, and implementation of immunoassay and LC-MS soluble biomarker assays for neuromuscular programs. Provide scientific and technical leadership, translate disease biology into assay strategies, evaluate new technologies, analyze and communicate data, manage cross-functional and vendor activities, and ensure documentation, data integrity, and compliance to support clinical decision-making.

Design, implement, debug, and optimize neuro-symbolic and deep learning AI systems; collaborate with engineers and subject-matter experts; lead R&D programs; write reports and papers; engage with customers and manage deployments.

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

Develop and maintain large-scale scientific workflows and tooling for computational drug discovery. Build cheminformatics pipelines, virtual screening and docking workflows, scalable ML inference and chemical databases, and automation for modeling, analysis, and visualization. Support scientists, increase automation, and ship features that advance AI-enabled proximity therapeutics.

Designs and operationalizes scalable machine learning platforms, pipelines, infrastructure, and production models. Develops MLOps and LLMOps solutions, including generative AI, prompt engineering, RAG, LLM fine-tuning, and computer vision applications. Collaborates with data scientists, engineers, architects, and cross-functional teams to optimize models and integrate them into enterprise systems. Applies hybrid ML and rule-based systems in regulated insurance environments, mentors colleagues, and supports Agile delivery.