Machine Learning Jobs in Cambridge, MA

Lead exchange optimization for Roku’s programmatic CTV advertising platform. Own strategies for dynamic price floors, traffic shaping, auction mechanics, deal optimization, and supply-demand forecasting. Partner with engineering, data science, and demand teams to productionize optimization models, run experiments, monitor exchange health, and improve revenue, fill rate, latency, win rate, and user experience. Define technical product requirements, guide roadmap execution, and communicate strategy to executives and industry partners.

This role involves owning customer engagements, building demos, performing technical discovery, and creating reusable assets in AI solutions.

Patent Counsel II manages patent prosecution and intellectual property strategy for molecular diagnostics, sequencing, bioinformatics, AI/ML, software, and computational biology technologies. The role drafts and prosecutes domestic and international patent applications, conducts patentability and freedom-to-operate analyses, coordinates outside counsel, advises on trade secrets and publications, supports licensing and litigation matters, and counsels scientific, technical, and business stakeholders on IP risks and opportunities.

Leads cardiovascular disease research using human ESC/iPSC and zebrafish models, automated high-throughput imaging, drug screens, biomarker discovery, and machine-learning analysis. Designs and executes complex experiments, troubleshoots workflows, interprets translational data, manages industry collaborations, and provides scientific leadership. The role contributes to publications, funding applications, strategic planning, and mentoring junior staff while serving as an internal expert in automated imaging and computational analysis.

Develop, deploy, and maintain machine learning and deep learning algorithms for EEG, cardiopulmonary, and other biosignal data used in medical devices and precision medicine. Lead the full algorithm lifecycle, including requirements, data curation, experimentation, validation, production deployment, documentation, testing, and maintenance. Improve internal ML tooling, apply DSP and statistical methods, present technical results, and support client-facing projects in regulated healthcare contexts.

Leads global health economics and value assessment strategy for Sanofi’s early neurology pipeline, including Alzheimer’s, AMD, and neurodegenerative assets. Oversees HEOR, real-world evidence, health economic modeling, evidence synthesis, and scientific publications. Partners with commercial, market access, regulatory, US HEVA, academic, and payer stakeholders to influence development, pricing, reimbursement, and business decisions. Mentors team members, presents to senior leadership, engages external experts, and ensures scientific rigor, compliance, and strategic impact.

Lead ML engineer responsible for architecting, building, deploying, and operating production-scale machine learning systems. Collaborate with product and data science teams to design models, data pipelines, CI/CD, and cloud architectures; retrain and monitor models; ensure performance, reliability, governance, and explainability; and mentor or lead engineering teams.

Lead statistical design and analysis for analytical and clinical validation studies of NGS-based cancer diagnostic tests. Develop statistical and machine learning methods, prepare regulatory submissions, ensure analytical quality, collaborate cross-functionally, and mentor junior biostatisticians. Support protocol development, statistical analysis plans, data reporting, regulatory agency interactions, scientific publications, and diagnostic assay development and approval.

Lead strategy, vision, and roadmap for a cross-functional squad across Everand and Fable. Drive product development for recommendations, search, and ranking systems, balance experiments and large investments, partner with engineering, design, research, and data to ship features that help readers discover books.

Develop and deploy machine learning models and active-learning workflows for complex fluids and soft-matter formulations. Connect composition, microstructure, processing, and bulk fluid properties, incorporate mesoscale/continuum simulation outputs, partner with experimental teams, and communicate model behavior and recommendations to cross-functional collaborators to accelerate formulation discovery.

Own and expand a portfolio of enterprise health system accounts, serve as executive sponsor, drive retention and growth, build expansion strategies, lead account planning and QBRs, partner with Product and Engineering to accelerate time-to-value, and translate customer needs into product and GTM insights.

Design, build, and productionize agentic AI systems including LLM orchestration, retrieval, and evaluation. Work across the ML lifecycle from experimentation to deployment and monitoring, leverage proprietary structured and unstructured financial data, and collaborate with data, product, design, and MLOps teams to deliver scalable, robust agentic solutions.

Leads Scribd’s content intelligence and UGC supply portfolio, owning corpus classification, metadata, quality, gap analysis, AI infrastructure, contributor experiences, and content acquisition strategy. Partners with ML, engineering, data science, consumer product, and business development teams to connect content supply with business value. Manages senior product leaders and established engineering and analytics programs while setting portfolio roadmaps and representing content strategy with executives.

Own Talon.One’s product narrative, positioning, messaging, competitive intelligence, sales enablement, and go-to-market support for enterprise buyers. Develop collateral, battlecards, solution briefs, launch messaging, ecosystem positioning, and customer-driven insights. Partner with Product, Sales, Marketing, Partnerships, and Customer Success across distributed teams, translating complex technical capabilities—including AI and machine learning—into clear business value for retail and QSR markets.

Seller-doer solution architect who leads technical discovery, architects multi-vendor data and AI platforms, builds proposals and carries quota, then stays hands-on to guide delivery, write production code, and expand accounts across Snowflake, Databricks, cloud, and modern data tooling.

Lead cross-functional development of a low-latency control system for neutral-atom QPUs. Translate technical roadmaps into traceable requirements, define subsystem interfaces, manage testing and integration, coordinate timelines across theory and engineering teams, and convert R&D outputs into product specifications while communicating status and risks to stakeholders.

Lead end-to-end architecture for a major Generative AI platform: define reference architectures, integration contracts, NFRs, and reusable patterns (RAG, model serving, prompt/agent workflows). Partner with product, engineering, data science, cloud, security, and DevSecOps to ensure secure, scalable, compliant, and production-ready AI solutions. Conduct design reviews, proofs-of-concept, and drive platform governance and operational readiness.

This role manages institutional client billing operations, ensuring accuracy in fee calculations, oversight of reporting, and implementation of training programs while leading a team.

Lead and scale the nonclinical safety function for early development programs, define and execute phase-appropriate toxicology strategies, integrate AI/in silico predictions with traditional data, oversee post-IND GLP studies (including chronic, reproductive, carcinogenicity), establish translational biomarker and exposure-based modeling, manage CRO relationships, and lead regulatory strategy and submissions (IND, IB, DSUR, NDA/MAA) including presenting AI-derived safety data to health authorities.

Lead Kensho's AI partnerships and strategic client portfolio, driving partnership development, cross-functional deal execution, post-sale adoption, and commercial expansion of Kensho's APIs and AI products worldwide.

Lead assessment and secure adoption of AI/ML and GenAI systems for clients. Design security patterns and controls, perform assessments and pen tests, prototype AI-enabled security capabilities, ensure compliance (PII, privacy, regulatory), document protocols, and collaborate with cross-functional teams to productionize scalable AI-security solutions.

Design, implement, and scale end-to-end retrieval-augmented generation (RAG) pipelines. Build and optimize retrieval systems, embeddings, vector search, and LLM orchestration. Collaborate with product, design, and MLOps to productionize robust ML systems across large proprietary datasets.

Lead ML engineer responsible for productionizing ML systems: design, build, deploy, monitor, and scale models and data pipelines on cloud (AWS). Collaborate cross-functionally, apply MLOps best practices (CI/CD, testing, governance), and maintain high availability and explainable AI standards.

Conduct research in machine learning focusing on AI, develop models, design experiments, collaborate on product ideas, and mentor researchers.

Own strategy, roadmap, and delivery of revenue cycle management (RCM) products for dental practices. Translate dental insurance rules, CDT coding, and claims workflows into scalable features, prototype rapidly with AI tools, validate feasibility with engineering, and optimize for denial reduction, faster reimbursement, and workflow automation.