Top Hybrid Machine Learning Engineer Jobs in Boston, MA

Own robotic grasping intelligence by designing bespoke neural networks, building cloud training and evaluation pipelines, deploying models to robot fleets, and improving performance through field telemetry. Develop simulation-first manipulation strategies using robotics concepts including motion planning, kinematics, geometry, and perception. Collaborate with perception and motion-planning engineers while setting technical direction for a small applied ML team.

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

Implement and productionize ML research into performant C++ and Python systems, build ML infrastructure and training pipelines, design LLM/agent applications, and deploy AI workloads across edge, near-edge, and cloud environments while collaborating with data science and engineering teams.

Design and optimize on-vehicle perception inference: allocate CPU/GPU resources, compress and quantize large multimodal models, build TensorRT model conversion pipelines, and deliver production-quality low-latency C++/CUDA inference for power- and thermal-constrained vehicle SoCs.

The Machine Learning Scientist will build and integrate ML models, analyze data, design scalable pipelines, and ensure robust model testing.