onsite
Physical AI Engineer Model - 42dot
AI Engineer
Lead the design and deployment of end‑to‑end trajectory generation and decision‑making models that fuse generative AI with real‑world robotic and mobility control, enhancing safety and efficiency in autonomous driving systems.
About the role
Key Responsibilities
- Design, implement, and optimize end‑to‑end trajectory generation models using Python and PyTorch.
- Integrate Reinforcement Learning and Imitation Learning techniques to improve autonomous decision‑making in dynamic environments.
- Collaborate with robotics and control teams to translate AI outputs into real‑time vehicle actuation.
- Develop and validate motion planning pipelines that ensure safe, efficient navigation under complex constraints.
- Conduct rigorous testing, simulation, and field validation of models in realistic driving scenarios.
Requirements
- Strong background in machine learning, especially RL and IL, with hands‑on experience in PyTorch or TensorFlow.
- Proficiency in Python and experience building scalable AI pipelines.
- Solid understanding of motion planning, control theory, and autonomous driving architectures.
- Experience with generative AI models and their deployment in real‑time systems.
- Excellent problem‑solving skills and ability to work cross‑functionally in a fast‑paced environment.
Skills
pythonpytorchreinforcement learninggenerative ai