Hiring: Software Engineer, Robotics Simulation & AI Infrastructure Company: Qualcomm Location: San Diego, CA Job Posted Time: 2026-09-03 14:47:20 Target Skills & Keywords : CI/CD, Data Pipeline, Kubernetes, Machine Learning, Pub/Sub, PyTorch, REST, Reinforcement Learning, Systems Engineering, Warp About the job Experience: •10+ years. We calibrate level from your depth during the interview loop, so apply if you are anywhere in that range. •4+ years of Systems Engineering or related work experience. •3+ years of Systems Engineering or related work experience. •2+ years of Systems Engineering or related work experience. Required Skills: •This is first and foremost a simulation role — roughly 80% of the work is the simulator itself as a critical platform component. The remaining ~20% is AI infrastructure enablement: integrating simulation into the training, dataset, and deployment pipelines owned by the AI operations team, working with them rather than replacing them. •Design and build core simulator subsystems — scene representation and authoring, physics backends, sensor models, rendering — across the scenarios our robots work in: tabletop manipulation, legged locomotion, navigation and vision, and long-horizon, multi-stage tasks. •Profile and optimize simulation and training workloads — physics solvers, rendering, data pipelines — so interactive workstation sessions and training throughput at scale stay high. •Integrate and extend best-in-class open engines — GPU physics, USD/Hydra rendering, offline path tracing — behind clean, swappable interfaces. •Build high-throughput paths for policy training and synthetic data generation: vectorized environments, GPU-resident state, procedural scene variation, domain randomization, and ground-truth labeling — consistent from an interactive workstation session to scheduled headless runs in the cloud. •Make simulation a release gate: scenario suites, deterministic replay, benchmarks, and metrics that catch regressions before they reach hardware. •Stand up hardware-in-the-loop configurations: production robotics software running on Qualcomm silicon in communication with the simulator on the host workstation or cloud, and quantify where simulation and reality diverge — system identification, contact and actuator modeling, sensor noise, measured transfer results. •Partner with AI operations, perception, controls, and silicon teams, and own the design docs, reviews, tests, and APIs others depend on. Qualifications: •Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience. •OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience. •PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience. •Depth in two or three of these matters more than familiarity with all of them. If you're excited about this role but don't match every qualification, we encourage you to apply. •Robotics simulators or real-time 3D engines: MuJoCo/MJX, Isaac Sim or Isaac Lab, Newton, PhysX, Gazebo, Drake, Unreal Engine, or Unity. Candidates from games, VFX, or AV simulation are welcome — these skills transfer directly. •GPU programming and performance engineering: CUDA, Warp, Vulkan, compute shaders, or accelerator-aware data layout. •Machine learning for robotics: reinforcement learning at scale, imitation learning, robot foundation models and VLAs, PyTorch. •3D graphics and scene pipelines: OpenUSD composition, PBR materials, real-time and offline rendering, sensor simulation. •Robotics and distributed systems: ROS 2/DDS, URDF/MJCF, pub/sub and schema-driven wire formats, containers, cluster orchestration, and CI/CD for compute-heavy workloads. •Effective leverage of modern AI tools as a core engineering skill: frontier AI models, AI coding and agentic workflows, AI-assisted learning for ramping on new domains quickly, and building knowledge bases — personal or team — to accelerate on-boarding and future work. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!