Top Machine Learning Jobs in Boston, MA

Design, develop, and maintain algorithms for engineering applications, manage datasets, and implement machine learning workflows in an AI Copilot startup.

As a Lead Machine Learning Engineer, you'll design and implement machine learning applications, collaborate with teams, ensure model performance, and build cloud-based infrastructures.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Develop and scale machine learning systems for physiological signal processing. Design and train models, ensure compliance, and mentor team members while collaborating with cross-functional teams.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Lead Research Scientist in Machine Learning, you will develop AI/ML algorithms, lead teams, work on innovative problems, and communicate technical insights.

As a Staff Machine Learning Engineer, you'll design and productionize ML models, collaborate with various teams, and mentor junior staff, impacting mental health care accessibility.

The ML Engineer will contribute to the automated discovery engine, developing RL frameworks, synthetic data engines, and evaluating performance using proprietary datasets.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

Lead a team to advance performance marketing through machine learning and data-driven strategies, optimizing budget allocation and measuring impact.

The role involves building end-to-end modeling pipelines, developing models, delivering insights to stakeholders, and collaborating with a technical team in a fast-paced environment.

Lead and implement AI/ML platform solutions to enhance patient care by developing scalable systems, mentoring engineers, collaborating with cross-functional teams, and leveraging emerging technologies.

Lead training, evaluation, and deployment of ML models for scene understanding and behavior prediction in autonomous vehicles.

You will train, evaluate, and deploy ML models for scene understanding and behavior prediction in autonomous vehicles, while collaborating with engineers.

You will design and implement high-performance software while applying machine learning techniques to complex problems in electronic design automation.

Design and implement ML strategies for extracting insights from LiDAR and imagery data. Build pipelines for classification and measurement, and lead a small ML team over time.

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

Lead cross-functional ML/AI initiatives, drive technical roadmaps, mentor teams, and deliver impactful ML/AI solutions for business growth.

Build and deploy AI/ML models for various asset categories, design workflows, and quickly prototype solutions using customer data.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

Lead the design and analysis of experiments, develop ML models to improve player experiences, and effectively communicate insights to stakeholders.