Top Machine Learning Jobs in Boston, MA

Manage and lead a team of Analysts, focusing on marketing measurement, optimizations, and utilizing machine learning to enhance campaign performance for clients.

Lead and mentor a team of data scientists and engineers in delivering personalized machine learning systems, aligning projects with business goals, and promoting best practices.

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.

Lead the technical vision for Upstart's ML and simulations platform, modernizing infrastructure and mentoring a team while collaborating cross-functionally.

As a Lead Machine Learning Engineer, you'll design and scale ML infrastructure, collaborate across teams, and mentor engineers in AI and ML innovations.

Lead the design, development, testing, and deployment of AI software components, focusing on machine learning models and AI applications within a cross-functional team.

Design and deploy production-grade ML systems, integrate models into software pipelines, and develop features leveraging ML for optimization and prediction problems.

The role involves developing ML algorithms for health applications, collaborating with data scientists and engineers, and deploying systems based on various data sources.

Lead the design, development, and implementation of machine learning applications, focusing on architecture, model training, and deployment using emerging technologies.

Lead centralized Machine Learning efforts at Affirm, managing model development lifecycles, fostering AI adoption, and overseeing a team of ML professionals to enhance business outcomes.

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

As a Principal AI/ML Software Engineer, you'll lead ML technology strategy, develop innovative solutions, and influence technical decisions across the organization while guiding high-performing teams.

The Principal AI/ML Software Engineer will drive ML strategy and innovation, influence technical decisions, and lead cross-functional teams to develop complex ML solutions.

The Principal AI/ML Software Engineer drives ML technology strategy and innovation, develops solutions for complex problems, and leads cross-functional initiatives while shaping the technical vision and architectural frameworks for AI/ML.

Design, build, and deliver machine learning models and components. Ensure performance and monitor models in production as part of an Agile team.

The role involves designing, developing, and supporting AI and ML products, collaborating with teams to transform risk management and deliver value to customers through technology.

The Staff Machine Learning Engineer will define technical strategies, design ML models for document processing and risk assessment, and build scalable ML systems to protect Coinbase users' funds.

The Staff Machine Learning Engineer will utilize AI models, mentor team members, and enhance automation solutions across Coinbase's operations, focusing on machine learning to solve complex challenges.

As a Senior Machine Learning Engineer, you will design, build, and deploy large-scale ML systems to enhance Dropbox's AI features, collaborating with teams and mentoring peers.

The Machine Learning Manager will lead a team of engineers, drive project delivery, provide technical guidance, and foster a culture of innovation and experimentation in AI.

As a Senior Machine Learning Engineer, you will develop and deploy ML models, advocate for responsible AI, mentor colleagues, and integrate solutions into clinical workflows.

As a Senior Machine Learning Engineer in the Health team, you'll design and productionize ML systems for personalized health metrics, collaborating with data scientists and engineers to optimize performance and ensure service reliability.

As a Senior Machine Learning Engineer, you will design and implement scalable data and ML pipelines, collaborate with data scientists, and maintain systems for fraud and payment risk management.

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

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.