Senior ML Engineer (AI Research, Physical AI)
Tasks
- Build datasets and evaluation methodologies
- Create data quality pipelines and capture strategies
- Design machine learning models for robotic agents
- Develop research software and distributed training infrastructure
- Develop simulation environments for robotic platforms
- Develop vision-language-action architectures
- Document research outcomes and technical findings
- Implement scalable distributed training pipelines
- Prototype robotic manipulation and whole body control capabilities
- Research imitation learning and learning from demonstration
- Run sim to real experiments
- Train and evaluate reinforcement learning systems
Perks/Benefits
- Autonomy and ownership
- Career growth opportunities
- Continuous learning support
- Flexible work environment
- International collaboration
- Research experimentation culture
Skills/Tech-stack
Action Trajectory Optimization | CI/CD | Code review | Computer Vision | Data Quality | Distributed Checkpointing | Distributed Training | FSDP | FlashAttention | Generative Modeling | Imitation Learning | Isaac Lab | Isaac Sim | JAX | Learning from Demonstration | Machine Learning | Mixed Precision | Mixed-precision training | Mujoco | Multimodal Learning | Planning and control | PyBullet | Python | Quantization | ROS | Reinforcement Learning | Robot Learning | Sim-to-Real | Simulation | Testing | Trajectory Optimization | Transformer | Version control | Zero
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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