Top Machine Learning Engineer Jobs in Boston, MA

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

Develop multimodal large language models for urban driving environments, implement ML solutions, and validate algorithms using real-world data.

The role involves developing machine learning algorithms, optimizing LLM deployments, and managing deployment pipelines while mentoring team members.

Develop and deploy machine learning models focused on driving behavior using sensor data, collaborating with teams on insights and solutions.

Lead the design, development, and implementation of Generative AI applications, ensuring high performance and scalability in cloud-native environments. Collaborate with AI/ML teams to drive innovation and apply best practices in machine learning engineering.

Research and develop audio-focused DSP and machine learning algorithms; implement and evaluate published approaches; build ML training and evaluation infrastructure; collaborate cross-functionally to transition research into advanced product development for audio rendering, voice capture, and sound-centric experiences.

Design, deploy, and monitor scalable ML pipelines and production models using Azure cloud services. Build Generative AI and RAG systems, containerize and orchestrate deployments, collaborate with cross-functional teams, and document ML architecture and workflows.

The Principal AI/ML Engineer will lead the design, implementation, and deployment of AI systems, mentor junior engineers, and ensure model performance and reliability in production environments.

Lead the development of robot learning models, design simulation environments, optimize policies for real-world robots, and contribute to data lifecycle management.

Design, build, and productionize scalable ML systems for physiological time-series data. Collaborate with data scientists, engineers, and product teams to deploy reliable, low-latency inference services, improve ML pipelines, and maintain production uptime.

The Machine Learning Engineer Intern at Zoox will work on perception systems, developing algorithms for autonomous driving, collaborating with teams, and leveraging advanced machine learning models and datasets.

The Machine Learning Engineer will design and implement ML pipelines and productionize models, collaborating with scientists and engineers on scalable systems.

Develop and scale machine learning systems for physiological signal processing. Design and train models, ensure compliance, and mentor team members while collaborating with cross-functional teams.

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.

Develop and enhance behavioral models for road users in autonomous vehicles, optimizing perception models to support safe driving decisions.

The Senior ML Ops Engineer will build and maintain infrastructure for AI/ML at scale, manage machine learning models, and support team initiatives while ensuring code quality and engineering standards.

Design and develop large-scale AI systems for healthcare, focusing on ML infrastructure, real-time analytics, and collaboration with teams. Requires extensive experience in software engineering and AI.

The Staff Machine Learning Engineer will define and build ML capabilities, design production systems, and lead ML strategy in a high-growth AI cybersecurity company.

The Senior Software Engineer will develop ML training pipelines, maintain cloud systems, and optimize the ML lifecycle for dental products.

The Senior Software Engineer will lead technical areas, drive projects, and build AI/ML features using Python and Go while ensuring user-friendly experiences.

As a Senior Software Engineer, you'll enhance servicing decisions with ML models, improve experimentation, and scale decisioning systems for personalized borrower experiences.

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

Seeking a Machine Learning Engineer with 3 years of experience to develop and deploy ML systems, optimize models, and work collaboratively with teams to enhance ML capabilities.

Design, build, and scale ML platform components including training pipelines, serving, feature stores, and monitoring. Lead projects from design to deployment, improve system reliability and observability, mentor engineers, and collaborate with data science and infrastructure teams to enable reproducible production ML workflows.