Senior ML Engineer (AI Research, Physical AI)
Tasks
- Apply learning from demonstration techniques
- Build data quality pipelines and capture strategies
- Build robust research software
- Collaborate across research and engineering teams
- Contribute to technical strategy
- Create datasets and evaluation methodologies
- Design machine learning models for robotic agents
- Develop simulation environments
- Develop vision-language-action architectures
- Document research outcomes and publish
- Implement distributed training infrastructure
- Implement reinforcement learning and imitation learning
- Incorporate human demonstrations and simulation data
- Optimize action trajectories for intelligent agents
- Prototype dexterous manipulation and whole body control
- Run sim to real robotics experiments
- Train and evaluate large scale machine learning algorithms
Perks/Benefits
- Autonomy and ownership
- Career growth opportunities
- Continuous learning support
- Flexible work environment
- Innovative culture
- International team collaboration
Skills/Tech-stack
CI/CD | Computer Vision | Deep learning | Distributed Checkpointing | Distributed Training | FSDP | FlashAttention | Imitation Learning | Isaac Lab | Isaac Sim | JAX | Language Models | Machine Learning | Mixed Precision | Mixed-precision training | Mujoco | Multimodal Learning | Planning and control | PyBullet | Python | Quantization | ROS | Reinforcement Learning | Robotics | Sim-to-Real | Simulation | Teleoperation | Transformer Models | Version control | Vision Language Models | Vision-language | Zero
Education
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