Teams at Genesis

Build scalable infrastructure for robotics simulation, including workload management, environment frameworks, task interfaces, evaluation tooling, and real-to-sim pipelines. Collaborate with policy training and asset-generation teams to improve sim-to-real performance. The role requires extensive physics simulation expertise, particularly rigid body simulation or FEM, along with CUDA and GPU programming proficiency. Experience with robotics simulation platforms, synthetic data, asset pipelines, manipulation, humanoids, or embodied AI is advantageous.

Operate robots through teleoperation equipment during onsite data collection sessions. Follow predefined tasks and standard operating procedures, monitor robot behavior, identify unsafe or unexpected activity, and maintain safety and consistency during repetitive sessions. Provide session feedback, remain focused for extended periods, and collaborate with operations staff and session leads. The role is hands-on and execution-focused, with technical setup and hardware maintenance handled by other teams.

Build and optimize distributed foundation-model training infrastructure across multi-node GPU clusters. Profile data pipelines, GPU kernels, memory, networking, and CPU/GPU workloads to improve convergence speed and utilization. Develop CUDA, cuDNN, Triton, and custom kernel solutions integrated with PyTorch. Create monitoring and debugging tools for large-scale training runs and diagnose performance issues.