Top Machine Learning Jobs in Boston, MA

The Research Engineer/Scientist will advance decision-making in critical industries using optimization and machine learning, collaborating with product managers and engineers.

The Machine Learning Engineer will design, implement, and manage complex ML algorithms, focusing on computer vision and data analysis while collaborating with team members to transition algorithms to production.

The Principal Machine Learning Engineer shapes the machine learning strategy and architecture, leads initiatives, mentors engineers, and influences technical decisions at SharkNinja.

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

Lead machine learning projects, collaborate with business partners, and manage data processes from research to production to drive business impact.

Design and build ML features using LLMs, collaborate on technical architecture, and ensure safety and performance of deployments.

Design and develop geometry processing algorithms and simulation models, manage datasets, and enhance machine learning workflows for engineering applications.

The Senior Machine Learning Platform Engineer will build foundational components for ML models, mentor junior engineers, and optimize streaming pipelines. Responsibilities include enhancing ML infrastructure and ensuring data quality.

As a Machine Learning Intern, you'll prototype and evaluate ML systems, collaborate with teams, and analyze large datasets to improve user experiences.

Develop and apply ML methods to create psychological tools, collaborating with experts, building data pipelines, and integrating systems into real-world applications.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The Staff Machine Learning Engineer will architect and implement advanced ML solutions, lead ML applications in Messaging and Notification, and mentor engineers within Airbnb's AI innovations.

Join Trexquant as a Global Alpha Researcher to develop trading signals, implement research, and apply machine learning for alpha discovery.

Lead the design and delivery of large-scale machine learning systems, mentoring engineers while driving technical strategy and collaboration across teams in AEC solutions.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

The Machine Learning Intern will contribute to ML research, advancing methodologies in protein modeling while collaborating with cross-functional teams on a summer project under mentorship.

Lead and mentor ML engineers and data scientists, overseeing ML strategy and development of scalable models for healthcare applications.

As a Machine Learning Intern at Xometry, you'll design, build, and optimize machine learning models, analyze datasets, and collaborate with teams to integrate models into production systems.

The Engineering Manager, Machine Learning will lead a team focusing on 3D deep learning and computer vision, manage the ML roadmap, and implement best practices for MLOps pipelines.

As a Distinguished Machine Learning Engineer, you'll lead teams in developing and implementing scalable ML applications, mentor engineers, and drive innovation in the financial sector.

Design and build ML models, optimize data pipelines, lead teams, and support AI software components, while advancing AI capabilities for improved customer experiences.

The Senior Staff Machine Learning Engineer will develop AI-powered solutions, mentor engineers, and collaborate with cross-functional teams to enhance Airbnb's customer experience through advanced machine learning technologies.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

14-month paid apprenticeship combining Flatiron School Data Science coursework (20 hrs/wk) with 20 hrs/wk of paid engineering work. Contribute to production software, write testable code, participate in sprints and code reviews, support feature development, QA, and documentation while receiving mentorship and building an AI/ML-focused portfolio.