Senior ML Engineer, Manipulation
Tasks
- Build data collection pipelines
- Build recovery and fallback behaviors
- Define evaluation metrics and benchmarks
- Deploy and debug policies on physical robots
- Design manipulation policies
- Implement policy architectures
- Train imitation learning models
- Train reinforcement learning models
- Validate grasp to place performance
Perks/Benefits
Skills/Tech-stack
Action Chunking | Autonomous Rollouts | Behavior Cloning | Data Augmentation | Dataset curation | Diffusion policies | Grasp Estimation | Hardware deployment | Imitation Learning | Kinesthetic Teaching | Learned Motion Generation | Model Compression | Motion Generation | PyTorch | Python | Quantization | Regression testing | Reinforcement Learning | Robot Hardware Deployment | Robot hardware | Sim-to-Real | Teleoperation | TensorRT | Transformer Models | Vision-language | Vision-language-action
Education
Regions
Countries
States
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