Staff Engineer - Robot Learning, Embodied AI

Niantic Spatial builds spatial AI models and services so people and machines can reason, learn and act safely in the physical world. The Staff Engineer, Robot Learning will lead engineering for the real-to-sim product within the Embodied AI group, working alongside the group's General Manager and Product leader to address the sim-to-real gap in visual-spatial understanding and build the scalable real-to-sim stack for embodied AI. The role is based in the San Francisco office with three days per week in office.

Responsibilities

Sharpen the roadmap by bringing first-hand knowledge of customer pain, existing solutions, and the value of doing better to roadmap decisions; Own the technical requirements by guiding the team to design the real-to-sim stack pragmatically and making the final recommendation on what to build, integrate, and simplify; Benchmark the impact by working with the Real-World Test Lab to design and run reproducible evaluations of the real-to-sim stack's effect on policy transfer and real-world performance; Build and ship by leading engineering delivery, personally building critical features, keeping scope tight, and removing blockers; Raise the technical bar by setting a high standard for the team and deepening its understanding of robotics development and deployment

Requirements

Experience training, evaluating, and deploying robot policies in systems used by enterprise or government customers, with responsibility for performance in real operating conditions; Deep practical experience using simulation for policy training or evaluation, including tools such as NVIDIA Isaac Sim, Isaac Lab, MuJoCo, or equivalent, and diagnosing sim-to-real failures; Hands-on experience with reinforcement learning, imitation learning, or both, and with deep-learning frameworks such as PyTorch; A practical understanding of how visual perception and 3D scene representations affect robotics training, evaluation, and real-world performance; Experience running experiments on real robots, from an ambiguous hypothesis through to defensible results; Strong Python and C++ skills, with experience building reliable production software; A bachelor's degree or higher in a relevant field

Nice to have

Authored or maintained a public robotics benchmark; Helped take an early product to repeatable adoption across multiple customers; Built or substantially extended robotics simulation infrastructure, including scene authoring, domain randomization, or large-scale training and evaluation; Trained and deployed vision-based navigation or mobility policies, particularly in varied, unstructured environments; Built pipelines that turn real-world reconstructions into simulation-ready environments

Benefits

Annual bonus; Equity; Medical coverage; Dental coverage; Vision coverage; 401(k)