Top Remote Senior Machine Learning Engineer Jobs in Boston, MA

Design and build a machine learning platform, deploy ML models, collaborate across teams, and establish monitoring standards for AI solutions.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

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

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

As a Sr. Machine Learning Engineer, you'll develop ML solutions for healthcare, manage data pipelines, write production-ready software, and own ML services end-to-end.

Lead the development of ML solutions to enhance user experience at Babylist. Build recommender systems and personalization features from scratch, collaborating with a cross-functional team.

The role involves designing, optimizing, and deploying machine learning models for edge environments, focusing on computer vision. The engineer will collaborate with teams to integrate models and improve inference efficiency while mentoring peers and upholding company values.

The Senior Machine Learning Platform Engineer will develop ML models, mentor engineers, optimize systems, and enhance ML infrastructure at Coinbase.

The Senior Machine Learning Platform Engineer will optimize ML pipelines, mentor junior engineers, and improve ML infrastructure, focusing on performance and data quality.

Lead the design and implementation of AI/ML models to enhance risk and fraud management. Collaborate across teams to prevent fraud and account takeovers, mentoring senior engineers in technical excellence.

As a Senior Machine Learning Engineer, develop infrastructure for ML model deployment, collaborate with teams, and ensure model reliability and performance.

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.

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.

Develop and prototype new generative models for Pinterest Canvas, oversee training data collection, mentor junior researchers, and publish findings.

As a Senior Machine Learning Engineer on the Perception Team, you will define technology direction, architect solutions for autonomous vehicles, collaborate with team members, and mentor junior engineers, contributing to high-stakes projects in autonomous driving.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The role involves building a recommendation engine, designing ML systems, making data-driven decisions, and collaborating with leadership to enhance user experiences.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

The role involves building ML infrastructure, creating data pipelines, ensuring data quality, and collaborating with data scientists to optimize models.

Develop and optimize machine learning models and workflows to enhance insurance processes. Collaborate on model integration, monitoring, and improvement while driving innovation in modeling techniques.

The Senior Machine Learning Engineer will design and implement detection systems to improve email security, lead project execution, and mentor junior engineers.

The role involves building computer vision models, researching deep learning methods, handling large datasets, and implementing MLOps best practices.

Design and deploy machine learning models for autonomous vehicles, focusing on data tagging, dataset curation, and model validation.