Senior ML Engineer (AI Research, Physical AI)
Tasks
- Build embodied learning datasets and evaluation methods
- Collaborate to convert experiments into production solutions
- Create data quality pipelines and capture strategies
- Design machine learning models for robotics
- Develop multimodal perception language control architectures
- Develop research software and distributed training infrastructure
- Develop simulation environments for robots
- Develop technical strategy for new AI research opportunities
- Document research outcomes through publications and demos
- Incorporate human demonstrations into AI models
- Optimize action trajectories for intelligent agents
- Prototype robotic manipulation mobile robotics whole body control
- Research reinforcement learning and imitation learning for robotics
- Run sim to real experiments
- Train and evaluate robotic agent models
Perks/Benefits
- Autonomy and ownership
- Career growth opportunities
- Continuous learning support
- Flexible work environment
- Influence on AI physical systems development
- International collaboration
- Research driven innovation culture
Skills/Tech-stack
CI/CD | Code review | Computer Vision | Continuous integration | Control Systems | Deep learning | Distributed Training | FSDP | FlashAttention | Generative Modeling | Imitation Learning | JAX | Language Models | Machine Learning | Mixed Precision | Mixed-precision training | Multimodal Learning | Planning | Python | Quantization | Reinforcement Learning | Robotics | Testing | Transformer | Version control | Vision Language Models | Vision-language | Vision-language-action | Zero
Education
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