Top Machine Learning Jobs in Boston, MA

As an AI Engineering Manager at PwC, you will lead the design and operation of AI-powered platforms, mentor engineers, and ensure project delivery excellence while focusing on security and scalability.

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.

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.

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 the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

Manage AI engineering teams and client relationships, drive project deliverables, mentor staff, and uphold quality standards while leveraging advanced technologies.

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 end-to-end machine learning projects to improve customer engagement and retention. Build, test, and deploy models for user forecasting, personalization, and Casino engagement. Partner cross-functionally to scale solutions, mentor junior data scientists, and communicate model impact to influence product and marketing strategy.

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.

Lead the end-to-end demand-to-value pipeline for enterprise AI: identify high-impact use cases, make buy/build decisions, drive adoption, establish baselines and ROI, and build a team to scale business-facing AI delivery while providing credible technical evaluation of ML and generative AI.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.