Top Machine Learning Engineer Jobs in Boston, MA

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

As a Cloud Machine Learning Engineer at Hugging Face, you will build ML solutions leveraging cloud technologies, integrate models, design APIs, and contribute to documentation and community advocacy.

The Senior Full-Stack Engineer II will lead technical areas, build and scale AI applications, develop APIs and collaborate with cross-functional teams.

Lead design and implementation of LLM observability features: prototype and scale product capabilities for tracing, evaluating, and debugging generative AI systems. Work cross-functionally to influence architecture, mentor engineers, prioritize customer pain points, and drive product and engineering decisions for reliable, high-performance AI observability.

The Senior Lead Machine Learning Engineer will design, develop, and implement machine learning systems, collaborating with teams to solve business problems using machine learning applications.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

Design, develop, and deploy scalable ML software systems for healthcare. Collaborate with teams to improve products and ensure performance and reliability.

Lead the design and delivery of large-scale machine learning systems, mentoring engineers while driving technical strategy and collaboration across teams in AEC solutions.

The Principal Machine Learning Engineer will develop optimization algorithms, enhance LLM deployments, and collaborate with research teams on model performance and compression.

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.

Lead the development of advanced perception algorithms for self-driving vehicles. Collaborate and mentor engineers, optimize algorithms, and implement sensor fusion for robust perception systems.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

As a Machine Learning Engineer at Twilio, you will architect and maintain data pipelines, build ML training workflows, and collaborate with cross-functional teams to deliver compliant, resilient services, ensuring quality and performance.

The role involves developing AI technologies for customer support at Airbnb, leveraging ML systems to enhance customer experience through innovative solutions.

The Senior Software Engineer will lead technical areas, manage AI/ML projects, develop model services, APIs, and collaborate on design and UX to enhance cloud-based AI solutions.

As a Lead Machine Learning Engineer, you'll design and implement machine learning applications, collaborate with teams, ensure model performance, and build cloud-based infrastructures.

As a Software Engineer II, you'll develop backend systems, support ML platform features, collaborate across teams, and ensure system availability.

Design, develop, and deploy AI solutions focusing on Generative AI and autonomous systems. Collaborate with teams to optimize AI pipelines and drive innovation.

The Senior AI/ML Engineer will architect multi-agent workflows, build evaluation frameworks, and mentor teams, focusing on integrating advanced AI with global risk data.

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.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

The Machine Learning Engineer will design, build, and maintain scalable ML systems, optimize ML pipelines, implement MLOps, and collaborate with teams to deploy models into real-time products.

As a Senior AI Engineer, you will develop and optimize Generative AI applications, manage AI pipelines, collaborate with clients, and ensure production delivery with MLOps best practices.

Build and maintain MLOps pipelines, deploy and monitor ML models as scalable services, transform and integrate healthcare data (FHIR/HL7), ensure reproducible feature management, and uphold HIPAA/HITRUST security for production ML in clinical systems.

The role involves developing, adapting, and implementing machine learning algorithms for computer vision tasks in power grid analysis. Responsibilities include experimentation, error analysis, and project ownership.