Top Remote Senior Machine Learning Engineer Jobs in Boston, MA

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

The Senior Machine Learning Engineer will develop AI workflows, collaborate with teams on models and pipelines, conduct research, mentor junior members, and innovate solutions for healthcare.

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.

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.

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.

Design and deploy machine learning solutions across AI use cases, working with cross-functional teams to translate healthcare challenges into scalable systems.

The Senior Machine Learning Engineer will design, build, and lead strategies for risk detection models, mentor team members, and apply advanced AI/ML methodologies to enhance user security and experience.

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

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

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.

As a Senior Machine Learning Engineer, you'll design and implement deep learning models and robust infrastructures for clinical applications, particularly in computer vision for dental conditions.

Design and implement AI solutions to enhance drug development, working with scientists and engineers to solve complex data problems.

Develop and optimize machine learning algorithms for LLMs, collaborate on research and engineering solutions, and manage deployment pipelines.

As a Senior Machine Learning Engineer, you will design and implement ML systems for conversational AI and intelligent automation, collaborating with cross-functional teams and mentoring colleagues.

The Sr. Machine Learning Engineer will build tooling and services for ML and generative AI solutions, focusing on deployment, evaluation metrics, and cross-functional collaboration.

The Senior Machine Learning Engineer will build and operate ML systems, manage the model lifecycle, and mentor team members while ensuring sustainability data accuracy.

As a Senior Machine Learning Engineer, you'll design and deploy ML models for real estate media while collaborating across teams to optimize solutions and improve user experience.

The Machine Learning Engineer will develop and deploy large language models focused on preprocessing datasets, training, fine-tuning, and maintaining ML pipelines, primarily in healthcare settings.

Design and develop edge AI firmware for camera systems, ensuring accurate AI algorithms, collaborating on architecture, and mentoring engineers.