Role at a glance
- Salary
- $224K – $431.3K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 12+ years of relevant professional experience encompassing large-scale ML training, AV systems, simulation, and AI infrastructure...
- Education
- Bachelor's degree in Computer Science, Robotics, Engineering, or a related field (or equivalent experience).
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Role Summary
NVIDIA's Autonomous Vehicles Simulation team is developing a closed-loop simulation-based reinforcement learning framework to train advanced end-to-end autonomous vehicle models, including Alpamayo R1. The role focuses on improving reinforcement learning and simulation accuracy and performance while collaborating with the AV Platform, AV Product, and Research teams.
What You'll Do
- Lead the design and development of large-scale RL training frameworks for multi-modal AV foundation models.
- Design, build, and optimize simulation and data processing pipelines for scalable training of driving policies.
- Measure and enhance simulation quality and refine the reward function for RL training.
- Develop monitoring and debugging tools to support reliable and performant training workflows on large GPU clusters.
- Integrate state-of-the-art model architectures into efficient and scalable training pipelines in partnership with researchers.
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View full postingQualifications
Bachelor's degree in Computer Science, Robotics, Engineering, or a related field (or equivalent experience); 12+ years of relevant professional experience; deep proficiency in RL algorithms, including PPO and GRPO; exceptional programming skills in C++ and Python; extensive experience with large-scale GPU clusters, HPC environments, and job scheduling/orchestration tools.
Required
- 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...
- Deep proficiency in RL algorithms, such as PPO and GRPO, including practical experience with hyperparameter tuning and reward function...
- Exceptional programming skills in C++ and Python
- Extensive experience with large-scale GPU clusters, High-Performance Computing (HPC) environments, and job scheduling/orchestration...
Preferred
- 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
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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. This position will design and improve the accuracy and performance of the RL framework and simulation, leveraging SOTA techs including NuRec, Traffic Models, and Cosmos World Model. 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.
What we need to see:
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).
Ways to stand out from the crowd:
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.
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.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.