Top Tech Jobs & Startup Jobs

Design and implement embedded control stacks, motion planning, and trajectory optimization for dynamic robots. Build real-time state-estimation pipelines fusing heterogeneous sensors, formulate and solve optimal control problems (nonlinear MPC, convex/trajectory optimization), create modular sim-to-hardware software, and lead on-robot debugging, tuning, and validation of controllers.

Own and scale end-to-end physical-data collection operations: scheduling, operator utilization, station uptime, throughput and quality. Recruit and develop operators and shift leads, standardize playbooks and SOPs across sites, partner with Quality and Annotation teams, stand up partner-site deployments, and build reporting that tracks collected hours, quality, and cost.

Design, build, and optimize distributed PyTorch training systems for multi-node GPU clusters. Profile and eliminate performance bottlenecks across data pipelines to GPU kernels, implement low-level CUDA/cuDNN/Triton kernels, tune CPU/GPU/memory/network utilization, and develop monitoring and debugging tools for large-scale training runs.

Design and maintain foundational platform frameworks and internal tooling to accelerate AI research. Collaborate with cross-functional engineering and research teams to build modular, reusable systems, improve workflows, ensure high code quality, and implement organization-wide, low-disruption changes.

Develop and optimize a learning-based robotic manipulation control stack; design and maintain low-latency teleoperation systems; train and deploy policies using reinforcement and imitation learning; diagnose control-pipeline latency and sim-to-real gaps; co-optimize simulation and real-world robot behavior; collaborate on building general-purpose Physical AI.

Design, build, and optimize distributed PyTorch training systems for multi-node GPU clusters. Profile and eliminate performance bottlenecks across data pipelines, kernels, and networking. Implement low-level CUDA/cuDNN/Triton kernels, tune hardware-software interactions, and develop monitoring and debugging tools for large-scale training runs to maximize utilization and reduce time-to-convergence.

Build and maintain scalable simulation infrastructure and environment frameworks for robotics model development, evaluation, and iteration. Create sim-ready digital twins, tune physics/rendering to reduce sim-to-real gap, and develop tooling for reliable, observable simulation workflows. Collaborate with simulation engine, rendering, asset, AI, and robotics teams.

Design, build, and operate large-scale distributed systems to improve reliability, scalability, and efficiency. Automate toil, perform capacity planning and performance analysis, prevent incidents, and provide cross-team technical leadership to balance system health with product velocity.

Own customer-facing go-to-market for robotics: identify design partners, drive pilots to production, manage complex technical sales, translate customer insights to product and engineering, define pricing and deployment playbooks, and build long-term partnerships in operational environments.

Design, prototype, and build robotic hardware systems; develop scalable data-collection platforms; improve simulation fidelity via system identification; maintain in-house hardware infrastructure; collaborate with engineering and simulation teams to deliver robust, scalable physical AI systems.