Top Tech Jobs & Startup Jobs in Boston, MA

Design, prototype, test, and support rugged mechanical systems for robotic sensing and compute platforms. Responsibilities include CAD assemblies, structural and thermal analysis, sensor mounts, ingress protection, material selection, DFM/DFA, mechanical drawings, GD&T, BOMs, prototyping, shock and vibration testing, thermal validation, vendor coordination, QA, field debugging, and production scaling. The intern will collaborate across mechanical, electrical, compute, and systems engineering teams.

Develop and train whole-body loco-manipulation policies for humanoid robots, deploy learned behaviors to physical hardware, improve motion retargeting and simulation fidelity, and build scalable evaluation and robot-learning infrastructure. The role bridges research and production engineering across reinforcement learning, simulation, control, perception, and hardware deployment.

Conduct research on humanoid manipulation, loco-manipulation, perception, planning, and control. Design and evaluate robotic systems in simulation or hardware, support robotics foundation-model data pipelines, and integrate manipulation data into learning frameworks. Collaborate with researchers, engineers, teleoperators, and field teams on hardware bring-up and autonomy goals. Contribute to academic publications and conference presentations.

Conduct research on humanoid manipulation, loco-manipulation, perception, planning, and control. Design and evaluate robotic systems in simulation or on hardware, support robotics foundation-model data pipelines, and collaborate on hardware integration, teleoperation, and autonomy. The internship emphasizes embodied intelligence, real-world experimentation, and publishing research in leading robotics venues.

Architect and develop high-fidelity multi-robot simulation environments and fleet orchestration systems. Build realistic physics, perception, communications, task allocation, planning, scenario generation, domain randomization, metrics, and experiment infrastructure. Calibrate simulations against real-world telemetry, automate regression benchmarks, and collaborate with robotics, infrastructure, DevOps, and field teams to deliver reliable, scalable, field-ready systems.

Develop and maintain AR/VR applications for supervising, manipulating, and controlling humanoid robots. Design spatial interaction workflows, integrate user interfaces with robotic perception and control systems, and deploy reliable applications on real robots. Prototype and evaluate interfaces through user studies, optimize distributed systems across headsets and robotic hardware, and collaborate with robotics, hardware, and software teams on testing, monitoring, and field support.

Develop and deploy learned manipulation models for humanoid robots, combining perception, planning, control, reinforcement learning, and imitation learning. Build robotics foundation models, scalable training and evaluation pipelines, data systems, and experimental infrastructure. Test systems on real hardware and in field environments, collaborating across research, engineering, and field teams to deliver reliable, generalizable robotic autonomy.

Conduct research on large-scale learned humanoid manipulation and robotics foundation models. Develop architectures, learning objectives, reinforcement and imitation learning methods, multimodal behavior models, and cross-embodiment transfer techniques. Design rigorous benchmarks and real-world experiments, train and deploy models on physical humanoid robots, analyze failures, and translate findings into scalable systems. Provide technical leadership, mentor colleagues, and communicate results through reviews, publications, presentations, and open-source work.

Own infrastructure for humanoid robotics research, including CI/CD, containerized builds, simulation and hardware-in-the-loop testing, Airflow data pipelines, dataset registries, and AWS infrastructure managed as code. Operate Kubernetes, ECS, Batch, RDS, S3, networking, secrets, observability, and access controls. Establish compliance, reproducibility, lifecycle policies, documentation, and runbooks while supporting researchers and coordinating infrastructure reuse with platform and cloud teams.

Lead and scale in-house data operations for robotics R&D: build and maintain data tooling and sensor hardware, run collection and annotation, manage interns/contractors, write SOPs and QA, and support demos and live troubleshooting.