Senior Machine Learning and Simulation Engineer - Autonomous Vehicles at NVIDIA

You are a seasoned machine learning expert with a bachelor's degree and over 12 years of professional experience building large-scale AI infrastructure and auto

Work type: onsite

Location: US, CA, Santa Clara

Type: Full-time

Summary

You are a seasoned machine learning expert with a bachelor's degree and over 12 years of professional experience building large-scale AI infrastructure and autonomous vehicle systems. You possess deep technical proficiency in reinforcement learning algorithms and high-performance computing environments. **What makes it worth a look...** NVIDIA is hiring for this senior role in Santa Clara, California, offering a base salary range between $224,000 and $431,250 depending on the level, plus equity and full benefits. You will lead the development of closed-loop simulation frameworks for training advanced foundation models used in autonomous driving. **You might be a good fit if you...** * Have extensive experience working with large-scale GPU clusters and orchestration tools like Kubernetes or SLURM. * Are highly skilled in C++ and Python for developing efficient, production-grade data pipelines. * Understand reinforcement learning theory, specifically PPO and GRPO, including complex reward function design. * Have a track record of scaling ML training frameworks in an industrial setting.

Job Description

We are seeking exceptional Senior Machine Learning and Simulation Engineers to join NVIDIA's Autonomous Vehicles (AV) Simulation team! This role requires strong technical leadership and outstanding software engineering skills, coupled with deep expertise in both simulation and artificial intelligence, including deep learning, reinforcement learning, end-to-end driving and Physics AI models. The successful candidate will have a solid track record of productizing ML solutions for autonomous driving and simulation at scale.

This position centers on developing a Closed-Loop Simulation-based Reinforcement Learning (RL) framework in order to train advanced end-to-end AV models, such as[ Alpamayo R1](https://research.nvidia.com/publication/2025-10_alpamayo-r1). This position will design and improve the accuracy and performance of the RL framework and simulation, leveraging SOTA techs including[ NuRec](https://docs.nvidia.com/nurec/index.html),[ Traffic Models](https://research.nvidia.com/labs/avg/publication/zhang.karkus.etal.cvpr2025/), and [Cosmos World Model](https://www.nvidia.com/en-us/ai/cosmos/). Success in this role requires close collaboration with the AV Platform, AV Product, and Research teams.

What you will be doing:

• Lead the design and development of large-scale RL training frameworks to accelerate the development of multi-modal AV foundation models.

• Design, build, and optimize simulation and data processing pipelines to enable scalable training of driving policies.

• Focus on measuring and enhancing simulation quality and refining the reward function for RL training.

• Ensure the reliability and performance of training workflows on large GPU clusters through the development of robust monitoring and debugging tools.

• Partner with researchers to integrate state-of-the-art model architectures into efficient and scalable training pipelines.

• Bachelor's degree in Computer Science, Robotics, Engineering, or a related field (or equivalent experience).

• 12+ years of relevant professional experience encompassing large-scale ML training, AV systems, simulation, and AI infrastructure development.

• Deep proficiency in RL algorithms, such as PPO and GRPO, including practical experience with hyperparameter tuning and reward function design.

• Exceptional programming skills in C++ and Python, vital for developing efficient systems and data pipelines.

• Extensive experience with large-scale GPU clusters, High-Performance Computing (HPC) environments, and job scheduling/orchestration tools (e.g., Kubernetes, SLURM).

• Experience in RL infrastructure or general LLM training/fine-tuning infrastructure in industry.

• Experience in simulation & closed-loop evaluation of autonomous driving end-to-end models.

• Proven record on large-scale data pipeline development and algorithm optimization.

You will also be eligible for equity and [benefits](https://www.nvidia.com/en-us/benefits/).

Applications for this job will be accepted at least until April 19, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

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