Applied Scientist, Navigation
Tasks
- Collaborate with cross functional teams to deliver perception capabilities
- Define and track perception system performance metrics
- Design develop and deploy perception algorithms for robots
- Drive end to end ownership of machine learning models
- Lead research in computer vision sensor fusion and 3D perception
- Mentor junior scientists and engineers
- Publish research findings and contribute to patents
- Train ML models for simulation and real world robots
Perks/Benefits
- 401k matching
- Adoption and surrogacy reimbursement
- Dental insurance
- EAP
- Flexible spending accounts
- Health insurance
- Mental health support
- Paid time off
- Parental leave
- Vision insurance
Skills/Tech-stack
3D Perception | Agent coordination | Artificial Intelligence | C++ | Computer Vision | Critical Systems | Depth Estimation | Diffusion Models | Fleet Level Navigation | Formal verification | Foundation Models | Gazebo | Image Segmentation | Imitation Learning | Isaac Sim | JAX | Java | Large Pretrained Models | Localization | Machine Learning | Mapping | Model-Predictive Control | Motion Planning | Mujoco | Multi-Agent | Multi-Agent Coordination | Navigation | Neural Motion Planning | Object Detection | Object Tracking | Optimization | Predictive control | Pretrained models | PyTorch | Python | ROS | ROS2 | Real Time | Real Time Robotics | Reinforcement Learning | SLAM | Safety-Critical | Safety-critical Systems | Scene Understanding | Sensor fusion | Sim-to-Real | Simulaton Environments | Trajectory Planning | World Models
Education
Roles
Regions
Countries
States
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