Top Machine Learning Jobs in Boston, MA

The Senior Applied AI/ML Scientist will lead the design and deployment of AI solutions, collaborate on impactful features, and enhance product capabilities by leveraging advanced AI and ML techniques.

The role involves developing AI technologies for customer support at Airbnb, leveraging ML systems to enhance customer experience through innovative solutions.

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.

You will lead technical strategy and engineering for ML-powered messaging features at Airbnb, integrating solutions and collaborating with teams to enhance user communication. Responsibilities include system design, mentoring, and establishing engineering standards.

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

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.

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.

The role involves collaborating across departments to build AI-driven models, optimizing data for decision support, and developing scalable solutions for business growth.

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.

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.