- Bachelor's degree in Computer Science, Robotics, Engineering, or a related field or equivalent experience.
- 10+ years of full-time industry experience in large-scale MLOps and AI infrastructure.
- 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).
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous research scientist with a genuine passion for advancing the state of AI? If so, we want to hear from you!
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.