Research Engineer Scientist Simulation Dyna Robotics San Francisco
Overview
As a Research Engineer Scientist focused on Simulation at Dyna Robotics you will build simulated worlds that power loco-manipulation policies. You own the pipeline from real-to-sim reconstruction through procedural scene generation to sim-based training data and evaluation for joint base motion and arm manipulation. This is a founding-type ownership role that defines its own research agenda.
What You'll Do11
- 1Build a pipeline that reconstructs real facility-scale environments into simulation including full rooms and aisles not just tabletop scenes
- 2Procedurally generate navigable environments that stress-test loco-manipulation policies across the range of spaces our robots operate in
- 3Generate synthetic training data for joint base positioning and arm manipulation policies feeding real-world failure modes back into new simulation scenarios
- 4Build simulation benchmarks testing joint base+arm policies using VLA imitation learning or diffusion models as a whole
- 5Push photorealistic rendering quality to close the sim-to-real gap for vision-based loco-manipulation
- 6Partner with AI Research team to accelerate policy development and collaborate with Data Ops on data capture priorities
- 7Simulate mobile bases such as wheeled tracked or holonomic platforms
- 8Familiarize with procedural scene asset generation domain randomization photorealistic rendering pipelines at scale
- 9Train/evaluate manipulation policies using imitation learning VLA diffusion or RL and understand simulated data flow
- 10Lead simulation efforts for wheeled mobile manipulators independent of fixed-arm tabletop or legged humanoid experience
- 11Apply strong Python skills with PyTorch or JAX for model training and evaluation
Requirements14
- 1MS or PhD in CS Robotics Graphics or equivalent hands-on experience
- 2Concrete experience with simulation stacks like MuJoCo Isaac Sim SAPIEN Omniverse Blender or similar for robotics or graphics
- 3Experience with procedural scene/asset generation domain randomization photorealistic rendering pipelines at scale
- 4Familiarity with training/evaluating manipulation policies such as imitation learning VLA diffusion or RL
- 5Experience simulating mobile bases including wheeled tracked or holonomic platforms
- 6Prior research or engineering background in loco-manipulation whole-body control or coordination of mobile-base motion with arm manipulation
- 7Strong Python skills comfortable with PyTorch or JAX for model training and evaluation
- 8Senior-level ability to define research agenda and exercise independent judgment on simulation leverage
- 9Bonus points for real-to-sim-to-real pipelines experience with NeRF Gaussian splatting differentiable rendering
- 10Exposure to world-model or video-prediction research as complement to classical physics simulation
- 11GPU-scale physics simulation experience with CUDA large-batch parallel simulation
- 12Background simulating wheeled mobile manipulators such as Boston Dynamics Stretch
- 13Publications at conferences like CoRL RSS ICRA NeurIPS CVPR or SIGGRAPH
- 14Experience leading or mentoring within a small research team
Salary Insight
Salary not disclosed in listing
Location
Required Skills
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