Top Tech Jobs & Startup Jobs

Design and rapidly fabricate mechanical, electrical, and sensor prototypes for robotics research. Collaborate with researchers and engineers to translate experiments into CAD, PCBs, wiring, sensor/actuator integration, and validated end-to-end prototype systems. Build fixtures, test rigs, and tooling; perform hands-on assembly, debugging, and documentation to support real-world deployments.

Design and optimize manufacturing processes for robotic systems, create fixtures/jigs/tooling, provide DFM/DFA feedback, maintain BOMs and build documentation, lead prototype-to-production transitions, perform RCCA/FMEA, track manufacturing KPIs, and implement quality control and test protocols.

Build and own the manufacturing and hardware-test software platform: convert procedures into repeatable workflows, implement local station software, integrate inventory and firmware management, ensure observability and resilience, automate tests, and debug across cloud, Linux stations, embedded devices, and test equipment.

Lead sourcing and supplier execution for the full robot BOM, build resilient global supply base, drive cost and should-cost improvements, manage CM transitions and NPI ramps, and ensure material continuity using MRP/ERP systems while partnering with engineering and executive leadership on supply risk and capacity planning.

The role involves integrating robot platforms into a fleet, defining and executing acceptance criteria, maintaining performance, and collaborating cross-functionally to improve system reliability.

This role involves executing cross-functional projects, driving partnerships, managing deployment efforts, and supporting communications with investors and external parties.

Design and implement control algorithms for robotics, develop real-time control loops, and debug complex hardware/software issues while collaborating with cross-functional teams.

As a Forward Deployed Robotics Engineer, you'll manage robotic systems' technical issues in real-world settings, performing diagnostics, collaborating with teams, and analyzing data for resolution and improvements.

As an ML Infra Engineer, you will optimize and scale training systems, manage GPU/TPU compute, and develop JAX training pipelines, collaborating with researchers for efficient model training.

Design and implement low-latency teleoperation interfaces and real-time video/streaming systems for on-site robots. Profile and optimize across drivers, networking, compute, and storage; build reliability, tracing, and debugging tooling; collaborate with researchers, hardware engineers, and operators to deploy dependable production robotics systems.