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.
Apply reinforcement learning to finetune multimodal LLMs.
Develop robust monitoring and debugging tools to ensure the reliability and performance of training workflows on large GPU clusters.
What we need to see
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 the pay of employees in similar positions. The base salary range is 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 August 9, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
