Machine Learning Jobs in Cambridge, MA

Serve as a customer-facing technologist partnering with sales to position, demo, and package Forrester AI solutions; translate technical AI capabilities into business value, support deal structuring and negotiations, develop enablement and adoption assets, gather product feedback from the field, and drive client retention through training and value realization.

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.

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.

Lead zero-to-one transformation of Scribd's knowledge platform using ML/LLMs. Set product vision, roadmap, and success metrics; prioritize trade-offs; partner with Design, Engineering, ML, and Data Science; deliver incremental improvements and extensible platform capabilities; drive cross-functional alignment and measure core user journeys.

Lead development of rigorous evaluation frameworks and metrics for autonomous systems, analyze large on-road and simulation datasets, detect metric drift, prototype statistical and ML methods, correlate simulation and real-world results, and drive actionable improvements to testing, sampling, and launch-readiness decisions while mentoring teammates and advising stakeholders.

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.

Build, deploy, and maintain production ML and AI systems (including LLMs, RAG, similarity search, guardrails, observability). Partner with cross-functional teams to design data pipelines, fine-tune models, monitor performance, and apply Responsible/Explainable AI best practices while contributing technical vision and roadmap for risk-focused AI products.

The Principal Scientist will lead AI/ML efforts in cancer biology, driving data science methodologies for oncology drug target discovery, collaborating across teams to enhance innovation and validate new therapeutic strategies.

Lead multimodal biomarker discovery by mining large clinico-genomic oncology datasets (bulk RNAseq, scRNAseq, WES/WGS, proteomics, epigenetics, imaging). Apply deep learning, ML, and statistical learning to build predictive models, collaborate with AIML and translational teams, and present findings to inform drug development and clinical strategies.

The role requires analyzing large datasets for biomarkers, integrating multi-omics data, and developing new statistical methods, collaborating with interdisciplinary teams.

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

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.

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.

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

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

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.

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.

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

Lead the development of AI-enabled data science solutions within ITS, enhancing investment outcomes through advanced analytics and machine learning, collaborating with investment teams to drive performance and risk management success.

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.

The Client Partner will manage strategic relationships with Life Sciences companies, focusing on commercial strategies, P&L management, and driving growth in analytics, AI, and cloud platforms.

The Account Director will manage client relationships, develop strategies, drive account planning, ensure client success, and generate revenue forecasts in the life sciences sector.

Lead product strategy, roadmap, and KPIs for BizzyCar’s agentic AI products. Own the AI Agent, collaborate cross-functionally throughout the SDLC, design rapid-cycle tests, gather requirements, commercialize features, and represent the company externally.