Top Machine Learning Engineer Jobs in Boston, MA

As a Senior Machine Learning Engineer, you will design, build, and deploy large-scale ML systems to enhance Dropbox's AI features, collaborating with teams and mentoring peers.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

As a Senior Staff Data Scientist/Machine Learning Engineer, you will develop machine learning models to enhance Autodesk's eCommerce platforms, drive data-informed decisions, and mentor junior team members.

The Senior Machine Learning Platform Engineer will optimize ML infrastructures, mentor junior engineers, and raise engineering standards for ML models and 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 maintain large-scale distributed training systems, optimize performance for ML models, and improve training efficiency.

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.

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.

Design and deploy machine learning models for personalized recommendations and search on Zillow's platforms. Collaborate with cross-functional teams to enhance user experience.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

As a Machine Learning Engineer, you'll evaluate neural network quality, coordinate with researchers, manage experiments, and report results to streamline AI software development.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

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

As a Machine Learning Engineer at Zillow, you will develop and implement machine learning models, prototypes, and algorithms, collaborating closely with scientists and engineers. You will focus on deploying applications, improving reliability, and fostering innovation in AI solutions.

As a Senior Principal Machine Learning Engineer, you will develop high-performance vLLM systems using Python and C++, optimize algorithms for inference, mentor engineers, and contribute to the vLLM open-source project.

The role involves developing distributed inference infrastructure using Kubernetes and programming in Go or Rust, alongside optimizing performance of LLM deployments and mentoring engineers.

As a Machine Learning Engineer, you'll build AI solutions from structured leadership data, develop RAG-based agents, and enhance the Leadership Intelligence Platform, focusing on efficiency and collaboration with research partners.

The Lead AI/ML Engineer evaluates emerging technologies, leads teams in adopting solutions, and provides technical leadership while mentoring junior specialists.

The Staff Data Scientist will develop machine learning models, advocate for a data-driven culture, mentor junior staff, and partner with cross-functional teams to enhance eCommerce personalization and drive data-informed decisions.

The Principal Machine Learning Engineer will develop multimodal technologies, mentor engineers, and drive product innovation in agentic AI systems.

As a Machine Learning Engineer, you will optimize backend services, integrate ML models, collaborate with cross-functional teams, and support continuous improvement initiatives.

Lead the architecture and management of AI/ML infrastructure using Kubernetes and Terraform, optimizing hybrid environments for performance and scalability.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

The role involves designing and developing machine learning infrastructure and models, consulting on best practices, and building scalable services for AI integration.

The Machine Learning Engineer will design, develop, and deploy ML models using Google Cloud tools, focusing on Document AI and Vertex AI, ensuring scalable applications and efficient performance.