Top Machine Learning Jobs in Boston, MA

Lead AI engineering teams to design, develop, and deploy scalable, cloud-native machine learning and AI solutions. Manage client relationships, mentor staff, ensure quality, and drive adoption of modern tools and practices (Docker, Kubernetes, CI/CD, vector DBs, LangChain, cloud platforms).

Lead design and implementation of integration and platform architectures combining AI and blockchain to improve client performance. Analyze requirements, develop technical designs, lead large projects, validate outcomes with clients, direct and coach teams, drive enterprise architecture and cloud (Azure) strategies, and support feasibility studies and business process modeling.

Lead and manage data science initiatives: develop ML/DL models, oversee data pipelines and lakes, validate data quality, coach team members, liaise with stakeholders, and ensure projects meet timelines, budgets, and client expectations while promoting innovation.

Lead teams to apply advanced data science and machine learning to large-scale claims, clinical, and member data to generate actionable insights that reduce cost of care and improve population health. Manage client relationships, secure project delivery, mentor staff, present findings to senior stakeholders, and help develop innovative analytics products for payer strategies.

Develop and apply statistical analyses, machine learning, and ML/DL/NLP techniques to extract insights from large datasets, build predictive models, design data solutions and visualizations, ensure data pipeline integrity, collaborate with clients, and mentor junior team members in PwC's Assurance practice.

Lead development and implementation of AI/ML solutions, transform data into insights, design and optimize models, manage projects and budgets, supervise and mentor teams, maintain quality and client relationships, and drive innovation across analytics engineering initiatives.

Lead development and delivery of production-grade AI solutions, advise on large-scale projects, manage and coach high-performing teams, collaborate with stakeholders, analyze complex data for innovation, and ensure adherence to technical and professional standards.

Manage an AI Quality engineering team to define technical strategy, architecture, and metrics; build testing frameworks for model drift and performance; oversee vendor integrations; drive engineering productivity improvements; and mentor team members.

Ten-week, full-time paid Data Science internship (June–August 2027) working on machine learning, deep learning, and large-scale data analysis. Interns evaluate modeling tools, integrate internal and external data/APIs, design data science models, and present insights to stakeholders. In-person attendance at an assigned U.S. location is required; interns may be considered for full-time roles after graduation.

Ten-week, full-time paid Data Science internship for current PhD students. Interns will build and evaluate modeling and analytics tools, integrate internal and external data sources, design data science models, and communicate results. Candidates must continue their PhD after the internship and may be evaluated for full-time roles upon graduation.

Lead data science projects to advance drug development, implementing models for patient selection and clinical trial optimization, and collaborating with cross-functional teams.

Lead data science projects to optimize drug development, develop AI models for clinical trials, and collaborate with teams on biomedical workflows.

Develop and scale machine learning systems to enable AI coaching, collaborate across teams for member insights, and contribute to architectural decisions.

The Senior Machine Learning Engineer designs and develops ML systems, collaborates with teams to meet analytical needs, and optimizes large-scale ML solutions while setting monitoring and best practices.

Lead and grow a team building Klaviyo's Customer Agent conversational AI platform. Set technical direction, own roadmap, collaborate cross-functionally, guide system and model design, ensure reliability, hire and develop engineers and managers, and deliver scalable, AI-driven customer engagement features.

Lead and direct multidisciplinary teams to research, develop, test, integrate, and demonstrate advanced signal processing, optimization, and machine learning algorithms for radar, electronic warfare, and sensor systems. Oversee modeling/simulation, algorithm T&E, customer engagement, and technical briefings for defense and intelligence applications.

Lead and deliver large-scale AI/ML programs and the next-generation Generative AI platform. Build and grow a world-class TPM discipline, manage cross-functional delivery, mitigate technical risk, and drive execution across product, engineering, design, and data science to achieve business impact in regulated environments.

Lead program management for Core Algorithm Development, coordinating algorithm, data science, firmware, software, product, and validation teams to plan, validate, integrate, and release physiological algorithms while improving processes, mitigating risks, and reporting progress to executives.

Manage a team of ML engineers to build and optimize Affirm's economic decisioning engine using advanced ML techniques. Collaborate across teams, provide technical leadership, and mentor engineers while driving a cohesive long-term ML strategy.

Lead and scale a cross-functional AI and engineering organization that builds production-grade AI models, automated data pipelines, and LLM-driven workflows to power Samsara's GTM operations. Define a multi-year AI roadmap, set quality and review standards for model outputs, collaborate with execs across Engineering, Product, and RevOps, and hire and mentor managers and individual contributors to drive adoption and reliable automation across CRM, telemetry, and enterprise data systems.

Lead applied AI/ML initiatives, design and deliver production-grade software, develop secure high-quality code, troubleshoot, automate remediation, evaluate vendor architectures, champion best practices across engineering, and drive adoption of AI/ML, NLP, LLMs and streaming technologies.

The VP of Agentic Systems will lead data science research and development, focusing on AI systems to enhance cybersecurity operations, requiring strong leadership and collaboration across technical teams.

Lead WHOOP's strategy for transforming sensor data into real-time intelligence, managing teams, delivering features, and driving technical direction in machine learning and embedded systems.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.