Top Machine Learning Jobs in Boston, MA

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.

As a Principal Engineer specializing in AI/ML, you'll define the technology strategy, lead cross-functional initiatives, and develop innovative ML solutions while influencing technical decisions across the organization.

As a Machine Learning Engineer II, you'll design, implement, and test machine learning systems, collaborating with various stakeholders to enhance predictive applications.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

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 Staff Applied Machine Learning Engineer, you'll design and implement LLM applications, integrating ML features to enhance user experiences and scalable services.

Lead the development of AI-powered systems at Capital One, collaborating with cross-functional teams to deliver innovative machine learning solutions and optimize data pipelines.

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 Statistician will develop advanced statistical and ML algorithms, analyze atmospheric data, and conduct model sensitivity and validation tests.

As a Principal ML Engineer, you will establish the technical vision for personalization at Launch Potato and drive alignment across ML teams while solving complex challenges and mentoring engineers.

The Principal ML Engineer establishes the technical vision for personalization and designs ML solutions that drive company strategy. Responsibilities include solving ML challenges, leading cross-functional initiatives, and mentoring senior engineers.

Lead the technical vision for personalization at Launch Potato, architecting ML solutions and influencing strategy while mentoring senior engineers.

Lead the technical vision and strategy for personalization at Launch Potato, solving complex ML challenges and mentoring senior engineers.

The role involves designing and building ML applications, leading teams, and collaborating on data-intensive solutions using various technologies, while ensuring optimal performance and governance of ML systems.

The Senior Manager in ML Engineering will lead design and implementation of ML applications, optimize systems, and collaborate with cross-functional teams for data solutions.

The Machine Learning Scientist will develop models and systems for content metadata and discovery at Netflix, collaborating with teams to operationalize AI solutions. The role requires significant experience and collaboration with stakeholders.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.

The Principal ML Engineer will define and lead the ML architecture and strategy, solve complex challenges, and mentor engineers across the company.

Develop machine learning models to differentiate normal and attack behaviors, collaborate with security researchers, and analyze algorithm performance.

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.

Lead the Content Engineering team, defining technical strategies and architecture while driving large-scale ML projects and ensuring Trust capabilities on the Pinterest platform.

Develop electrical system ontology for data centers, utilize monitoring tools, create anomaly detection models, and collaborate with teams on insights and strategies for optimization.

Develop and implement advanced reinforcement learning methods and distributed systems for AI agents. Collaborate with customers to understand needs and create tailored solutions.

Lead the technical vision for ML systems focused on personalization, architecting solutions, solving complex challenges, and mentoring senior engineers.

Lead the development of AI-driven security workflows, integrate machine learning models, establish data pipelines, and mentor engineers.