Senior ML Engineer (AI Research, Physical AI)
Tasks
- Build pipelines for human demonstrations simulation data video and autonomous experience
- Collaborate with research and engineering teams to deliver solutions
- Create datasets evaluation methodologies and data quality pipelines
- Design machine learning models for robotic agents
- Develop research software and distributed training infrastructure
- Develop simulation environments and run sim to real experiments
- Develop vision-language-action architectures
- Document research outcomes and share technical reports publications and demonstrations
- Optimize planning methods guided generation and action trajectories
- Prototype dexterous manipulation mobile robotics whole body control
- Research reinforcement learning imitation learning and learning from demonstration
- Train and evaluate large scale machine learning algorithms
Perks/Benefits
- Autonomy and ownership
- Career growth opportunities
- Continuous learning support
- Flexible work environment
- Impactful AI research projects
- Innovative culture
- International collaboration
Skills/Tech-stack
Actor-critic | CI/CD | Computer Vision | Deep learning | Distributed Checkpointing | Distributed Training | FSDP | FlashAttention | Generative Modeling | Imitation Learning | Isaac Lab | Isaac Sim | JAX | Machine Learning | Mixed Precision | Mixed-precision training | Model-based reinforcement learning | Mujoco | Multimodal modeling | Offline Reinforcement Learning | Planning and control | Policy Optimization | Preference Learning | Proximal Policy Optimization | PyBullet | Python | Quantization | ROS | Reinforcement Learning | Reward Modeling | Robotics | Sim-to-Real | Simulation | Transformers | Version control | Zero
Education
N/A
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