Senior Research Engineer - Autonomous Vehicles
Core
Developing large-scale supervised and reinforcement learning training frameworks, simulation infrastructure, and sim-to-real pipelines for multi-modal foundation models in autonomous vehicles.
Role type
Senior Research Engineer (AI Infrastructure & MLOps)
Builds
Scalable training frameworks, GPU-accelerated simulators, and sim-to-real transfer pipelines for AV foundation models.
Domain
Autonomous Vehicles, Deep Learning, Reinforcement Learning, MLOps
Deliverable
production ML models
Required skills
Distributed training systems design, Reinforcement learning algorithms, GPU acceleration & CUDA, Cluster management (Kubernetes/SLURM), Python & C++ programming, Multimodal data processing, Simulation infrastructure development, LLM integration, Training pipeline optimization
Preferred skills
Experience with PyTorch/JAX/TensorFlow, Policy learning techniques (reward shaping, domain randomization), HPC environments
Technologies
PyTorch, JAX, TensorFlow, CUDA, Kubernetes, SLURM, Python, C++
Responsibilities
Develop large-scale training frameworks for multi-modal foundation models; Optimize GPU and cluster utilization for massive dataset training; Implement scalable data loaders for multimodal datasets; Build and optimize GPU-accelerated simulation infrastructure; Collaborate on integrating model architectures into training pipelines; Develop sim-to-real transfer pipelines for AV deployment; Propose scalable solutions combining LLMs with policy learning; Apply reinforcement learning to fine-tune multimodal LLMs; Develop monitoring and debugging tools for training workflows.
Seniority
Senior, hands-on IC
