Senior Research Engineer - Autonomous Vehicles

Details

NVIDIA is recruiting research engineers for its Autonomous Vehicles Research team. The role focuses on software engineering and artificial intelligence, including deep learning, reinforcement learning, generative modeling, autonomous driving, AI safety, closed-loop training, and AV foundation models such as vision-language and reasoning models. The position supports fundamental, publishable research while providing opportunities to influence products and collaborate with teams working on CUDA, physically based simulation, graphics, natural language processing, autonomous driving, hardware optimization, robotics, and healthcare.

Responsibilities

• Develop large-scale supervised learning and reinforcement learning training frameworks for multimodal AV foundation models 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 for multimodal datasets, including video, text, and sensor data.
• Build and optimize GPU-accelerated simulation infrastructure to support large-scale training of driving policies.
• Collaborate with researchers to integrate advanced model architectures into scalable training pipelines.
• Develop sim-to-real transfer pipelines and work with the AV product team to deploy systems to real-world vehicles.
• Propose scalable solutions combining large language models with policy learning.
• Apply reinforcement learning to fine-tune multimodal large language models.
• Develop monitoring and debugging tools to ensure the reliability and performance of training workflows on large GPU clusters.
• Publish research at leading venues and communicate with teams and domain scientists across different areas.

Requirements

• Bachelor's degree in Computer Science, Robotics, Engineering, or a related field, or equivalent experience.
• At least 10 years of full-time industry experience in large-scale MLOps and AI infrastructure.
• Proven experience designing and optimizing distributed training systems using frameworks such as PyTorch, JAX, or TensorFlow.
• Deep familiarity with reinforcement learning algorithms such as PPO, SAC, and Q-learning, including tuning hyperparameters and reward functions.
• Familiarity with policy learning techniques including reward shaping, domain randomization, and curriculum learning.
• Deep understanding of GPU acceleration, CUDA programming, and cluster management tools such as Kubernetes.
• Strong programming skills in Python and a high-performance language such as C++.
• Strong experience with large-scale GPU clusters, HPC environments, and job scheduling or orchestration tools such as SLURM and Kubernetes.

Benefits

• Equity eligibility.
• Employee benefits.
• Opportunity to conduct groundbreaking, publishable research in an open and collaborative research environment.

NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer. Applications will be accepted at least until January 13, 2026. This posting is for an existing vacancy.