NVIDIA is looking for research engineers to advance AI models for autonomous vehicles, focusing on areas like deep learning, reinforcement learning, and generative modeling to solve complex challenges in AV development and deployment.
Requirements
- Proven experience designing and optimizing distributed training systems with frameworks like PyTorch, JAX, or TensorFlow.
- Deep familiarity with reinforcement learning algorithms like PPO, SAC, or Q-learning, including experience tuning hyperparameters and reward functions.
- Familiarity with common policy learning techniques like reward shaping, domain randomization, curriculum learning.
- Deep understanding of GPU acceleration, CUDA programming, and cluster management tools like Kubernetes.
- Strong programming skills in Python and a high-performance language such as C++ for efficient system development.
- Strong experience with large-scale GPU clusters, HPC environments, and job scheduling/orchestration tools (e.g., SLURM, Kubernetes).
Responsibilities
- Develop large-scale supervised learning and reinforcement learning training frameworks to support multi-modal foundation models for AVs capable of running on thousands of GPUs;
- Optimize GPU and cluster utilization for efficient model training and fine-tuning on massive datasets;
- Implement scalable data loaders and preprocessors tailored for multimodal datasets, including videos, text, and sensor data;
- Build and optimize simulation infrastructure (based on GPU-accelerated simulators) to support the training of driving policies for AVs at scale;
- Collaborate with researchers to integrate cutting-edge model architectures into scalable training pipelines.
- Develop sim-to-real transfer pipelines and work closely with the AV product team to deploy to real-world cars;
- Propose scalable solutions that combine LLMs with policy learning.
Other
- 10+ years of full-time industry experience in large-scale MLOps and AI infrastructure.
- Communicating with different teams and domain scientists in different areas is essential.
- Are you a creative and autonomous research scientist with a genuine passion for advancing the state of AI?
