Top Machine Learning Jobs in Boston, MA

Design and implement AI systems and scalable machine learning models, perform data wrangling and software engineering to deploy AI solutions, interpret data for client recommendations, collaborate across teams, uphold technical standards, and build client relationships while navigating complex, ambiguous problems.

Develop data science solutions for Trust and Safety, including fraud and abuse detection. Responsibilities include gathering and preparing data, exploratory analysis, feature engineering, statistical analysis, machine learning, model evaluation, and communicating insights. The role partners with Product, Engineering, Operations, and Business stakeholders to deliver models, dashboards, recommendations, and operational improvements, with emphasis on rare-event detection and imbalanced datasets.

Leads product vision, roadmaps, prioritization, and delivery for enterprise data science enablement capabilities. Serves as Product Owner, translating customer and stakeholder needs into backlogs and technical solutions. Partners with data scientists, engineers, architects, and business teams to support AI/ML development, deployment, monitoring, adoption, and business value realization. Drives reusable platform capabilities, technical debt reduction, DevOps and MLOps improvements, Agile delivery, and executive communication.

Develop and implement radar-based perception and multi-target tracking algorithms for ADAS. Design extended object tracking and point-cloud processing, integrate algorithms into embedded real-time systems, perform validation and debugging, analyze test results, and collaborate with cross-functional teams to improve system performance.

Lead Data Scientist will define goals and metrics for algorithm Test & Evaluation, research T&E methodology, lead vendor coordination, present analyses and results to stakeholders, and transition algorithms into software and real-time embedded systems.

Lead technical vision and execution for AI/ML, decision systems, and mission planning programs. Manage multidisciplinary teams, ensure schedule and budget adherence, provide technical oversight, cultivate external partnerships, and pursue business growth while guiding program delivery and technical strategy.

Perform data analysis and test & evaluation of machine learning algorithms; develop algorithms for physical and autonomous systems; transition algorithms to software and embedded systems; work with stakeholders to present results and solutions; research new ML and data-analysis methods; handle large, multidimensional datasets and data pipelines.

Leads the Partnerships Customer Management Data Science team, mentoring specialists and owning the strategic roadmap for predictive modeling across credit risk, account usage, and portfolio financials. Oversees end-to-end machine learning model development, validation, and production implementation. Partners with analysts, engineers, and product managers while applying Python, AWS, Spark, H2O, and other technologies to analyze large-scale data and deliver customer-focused business outcomes.

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.

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 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 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.

Leads a data science team focused on customer intelligence and personalization across digital products, apps, newsletters, and marketing channels. Develops lifetime value, segmentation, retention, recommendation, attribution, forecasting, and engagement models. Owns product funnel analytics and experimentation, including A/B testing and causal inference. Partners with Product, Marketing, Editorial, Data Operations, and Engineering to translate customer behavior into product improvements, measurable growth, and scalable data capabilities.

Develops and productionizes deep learning and machine learning perception models for robotics and recycling sortation. Responsibilities include experimenting with neural network architectures, designing computer vision solutions, conducting statistical experiments, deploying successful models, collaborating with data, modeling, and cloud infrastructure teams, and improving ML infrastructure.

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Leads a data science team and personally drives analyses, experimentation, and product analytics to identify patient experience improvements. Partners with Product, Engineering, Research, and Data Engineering teams to develop product features, evaluate business and product performance, guide product planning, and translate statistical findings into actionable recommendations. Manages and develops analytical talent while applying data storytelling, A/B testing, marketplace metrics, and retention, conversion, engagement, and churn analysis.

Lead product strategy and execution for signals exploitation and tracking capabilities. Define roadmaps, shape backlogs with customers and product owners, support architecture and design reviews, and drive development and demonstration of advanced algorithms and software for DoD and Intelligence Community missions. Balance reuse, integrated system offerings, and component supply-chain opportunities while leading engineering teams through the Agile lifecycle and supporting technical marketing and business development.

Partner with healthcare clients to design, prototype, and deploy production-grade AI/LLM solutions. Lead discovery, architecture, cloud integration, and delivery while troubleshooting distributed systems and driving measurable client outcomes.

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.

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 teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

Drive go-to-market strategy and adoption for Kensho AI products by bridging technical AI capabilities and commercial teams. Lead customer demos, technical deep-dives, co-development partnerships, market analysis, and sales enablement while feeding product and strategy teams with market insights to expand revenue and partnerships.

Lead AI strategy, partner engagements, and operational execution across CrowdStrike products. Align R&D and product delivery to company AI strategy, prioritize initiatives, set organizational goals, drive thought leadership, and create order in complex cybersecurity AI environments while delivering customer value.