Machine Learning Jobs in Cambridge, MA

Lead development and validation of computational biomarkers and predictive models using multimodal biomedical data, including radiology imaging, clinical, molecular, pathology, and real-world datasets. Apply machine learning, statistical modeling, representation learning, foundation models, and causal inference for patient stratification, outcome prediction, and clinically actionable insights. Collaborate with radiologists, oncologists, data scientists, statisticians, and other experts while communicating findings, assumptions, uncertainties, and limitations through publications and presentations.

Leads quantitative research for infrastructure and real-assets investing, applying statistical models to private-market risk, returns, investment opportunities, portfolio construction, and fundraising support. Develops research plans, analyzes large datasets, communicates actionable insights to investment and client-facing teams, and incorporates AI and machine-learning techniques into investment processes.

The Senior Product Manager will lead the lifecycle of secure payment products, translating customer needs into requirements, driving cross-functional collaboration, and innovating through AI and ML.

Drive revenue growth by selling Splunk enterprise software to large accounts. Responsibilities include generating pipeline, meeting license, support, and service revenue targets, expanding customer relationships, orchestrating complex deals, leveraging channel partners, developing business plans, and communicating progress and obstacles to internal stakeholders.

Conduct market and competitive intelligence across Autodesk’s industries, analyzing AI developments, competitors, startups, funding, products, partnerships, research, and regulations. Partner with research teams to define markets, size opportunities, map competitors, test assumptions, and synthesize qualitative and quantitative findings. Lead projects, manage contributors and timelines, produce executive-ready briefs and presentations, and improve intelligence systems and processes using AI and automation with appropriate human validation.

Leads atomistic molecular modeling and molecular dynamics simulations for antibodies, small molecules, and other pharmaceutical modalities. Applies predictive science, data analysis, visualization, and data science workflows to drug development challenges. Collaborates with formulation, process, computational, and analytical scientists; develops dashboards and reports; manages projects and stakeholder alignment; and communicates research through publications and presentations.

Lead and build functional genomics analytics capabilities for CRISPR screens, single-cell perturbation studies, imaging, and multi-omics target prioritization. Develop computational, AI, machine learning, and image analysis methods; integrate genomic, transcriptomic, proteomic, and morphological data; establish reproducible and FAIR data practices; and guide discovery decisions. Lead, mentor, and collaborate with scientists, engineers, and external partners across therapeutic areas.

Design, build, test, and improve plugin-based forecasting models from business need through production deployment. Own ML and modeling initiatives end to end, evaluate performance across customer environments, distinguish generalizable solutions from customer-specific requirements, and use AI-assisted engineering tools. Work autonomously with customers and cross-functional stakeholders in a distributed international team, with occasional travel.

Develop and research novel machine learning algorithms for brain-computer interface applications. Improve brain activity identification, speed, accuracy, and muscle-artifact removal using real-time and large EEG datasets. Responsibilities include implementing and creating neural-network and other machine learning methods, rapidly prototyping features, collaborating with developers and the CEO, advancing intellectual property, documenting work, and contributing creatively in a fast-paced startup environment.

Drive data-informed decisions across carrier growth, product launches, user acquisition, and partnerships. Partner with marketing, product, and business development teams; design and analyze A/B experiments; identify scalable growth levers; conduct complex analyses using machine learning models; and automate manual processes to improve operational efficiency.

Leads data science, AI, digital health, and analytics strategy for Immunology R&D. Partners with scientific, clinical, platform, and engineering teams to identify use cases, analyze workflows, evaluate emerging technologies, develop scalable solutions, and improve research execution and decision-making. The role focuses on healthcare, imaging, clinical, biomarker, real-world, and digital health data, including generative and agentic AI applications.

The Business Operations Associate will drive data-informed decisions across growth, product, and business initiatives. Responsibilities include analyzing customer and partner performance, designing and evaluating A/B experiments, identifying profitable acquisition and partnership opportunities, leveraging machine learning models for insights, and automating manual processes to improve operational efficiency. The role partners with marketing, product, and business development teams and communicates findings to stakeholders ranging from frontline employees to executives.

Lead data-driven business operations and analytics initiatives across acquisition, partnerships, and product growth. Design and analyze A/B experiments, use machine learning and SQL for complex analyses, identify scalable growth levers, inform strategic decisions, and automate manual processes to improve operational efficiency. The role partners with marketing, product, and business development teams and communicates insights from frontline teams to the C-suite.

Drive data-informed decisions across growth, product, and business initiatives. Partner with marketing, product, and business development teams; design and analyze A/B experiments; identify acquisition and partnership growth levers; use advanced machine learning models for business analysis; and automate manual processes to improve operational efficiency. Communicate insights and recommendations to stakeholders ranging from frontline employees to executives.

Leads global biometrics strategy and a statistics organization across CVRM clinical development programs. Provides scientific oversight for study design, statistical analysis, clinical reports, regulatory submissions, and health-authority responses. Influences portfolio and investment decisions, drives quality and productivity improvements, supports responsible AI adoption, and builds organizational capabilities. Partners with senior leaders, regulators, and external experts across a global matrix, with responsibility for robust evidence generation throughout the drug development lifecycle.

Leads Autodesk’s enterprise GTM revenue analytics foundation, including KPI governance, semantic data models, reporting standards, dashboards, and executive insights. Partners with data, systems, finance, sales, marketing, and customer success teams to improve revenue decision-making. Defines AI-enabled analytics use cases and roadmap while ensuring scalable, secure, governed solutions. Serves as a technical and analytical leader, influencing cross-functional priorities and mentoring team members.

Designs and implements scalable finance solutions in Microsoft Dynamics 365 Finance & Operations. Leads fit-gap analysis, financial process optimization, integrations, reporting, project delivery, stakeholder engagement, training, and M&A finance activities. Partners with Finance, IT, data, and architecture teams to introduce automation, AI, Copilot, predictive analytics, and strong governance. Advises senior leadership, mentors analysts, and ensures financial systems support accurate reporting, compliance, and organizational growth.

Leads data management and technical delivery for life sciences consulting engagements. Develops predictive models and advanced analytics using large healthcare datasets, including claims, EHR, payer, sales, formulary, and coverage data. Builds internal tools, automates workflows, documents processes, presents insights to stakeholders, and coaches data engineers and junior staff. Supports pharma and biotech clients with product planning, pricing, reimbursement, commercialization, and regulatory solutions.

Develop and fine-tune foundation, generative, and perturbation models for single-cell and other biological data to support disease modeling, target identification, and drug discovery. Build interpretable models, deploy generative AI on cloud platforms, establish benchmarking frameworks, and collaborate with biology, chemistry, and omics researchers. The role also involves communicating technical concepts and may include developing agentic AI systems for scientific discovery.

Lead the design, validation, deployment, governance, and continuous improvement of machine learning and predictive analytics solutions for U.S. Commercial operations. Analyze claims, EHR, and commercial data to support patient identification, treatment adherence, provider engagement, and commercial strategy. Partner with Commercial, Medical Affairs, and analytics teams, communicate insights to executives, mentor data science professionals, and manage vendors and cross-functional initiatives.

Leads and develops a team of 4–6 Account Executives selling enterprise AI-powered safety and operations solutions. Responsibilities include coaching, pipeline management, forecasting, account planning, deal negotiation, customer health monitoring, cross-functional growth initiatives, and supporting strategic customer conversations across manufacturing, logistics, and warehousing markets.

The Sales Engineer in Financial Services coordinates with clients and internal teams, develops technical architectures, delivers presentations, manages implementations, and ensures customer satisfaction through technical support and product training.

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.

Senior leader responsible for analytical testing strategy across cell and gene therapy programs, including manual and automated methods, assay qualification, PAT, laboratory automation, informatics, data integrity, and stability testing. Leads cross-functional partnerships, regulatory-supporting documentation, operational best practices, reagent and assay control management, and organizational growth. Oversees budgets, headcount, recruitment, mentoring, and development of analytical testing, operations, and automation teams.

Develop scalable computational pipelines for biophysical modeling of neurons and neural populations. Apply machine learning and statistical inference to large-scale neural recordings, construct bio-realistic networks, and analyze complex time-series data. The role also involves shaping the technical roadmap, prototyping novel modeling approaches, and collaborating across neuroscience, experimental biology, and AI teams in an ambiguous R&D environment.