Senior Machine Learning and Simulation Engineer - Autonomous Vehicles
Santa Clara, CA, US
- Pay
Multiple pay amounts — pay source
#AutonomousVehicles 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: 224,000 USD – 356,500 USD for Level 5; and 272,000 USD – 431,250 USD for Level 6. You will also be eligible for equity and benefits.
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingLead design of large-scale RL training frameworks for AV foundation models
Design, build and optimize simulation and data pipelines for driving policy training
Measure and improve simulation quality and refine the RL reward function
Build monitoring and debugging tools for reliable training on large GPU clusters
Partner with researchers to fit new model architectures into training pipelines
From the employer’s posting
Lead the design and development of large-scale RL training frameworks
Design, build, and optimize simulation and data processing pipelines
Focus on measuring and enhancing simulation quality and refining the reward function for RL training.
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.
Education & alternatives
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:
Tools in this posting
- C++
- Python
- Kubernetes
Source — Tool mentions in context
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:
Posting record
Report an errorOpen 5 monthsWe first saw this posting 172 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- May 13, 2026 · 172 days ago
- Recorded sightings
- 245
- Last seen by us
- Oct 31, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
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Job description
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- Pay
#AutonomousVehicles 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: 224,000 USD – 356,500 USD for Level 5; and 272,000 USD – 431,250 USD for Level 6. You will also be eligible for equity and benefits.
- Location & working pattern
Santa Clara, CA, US
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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