Senior/Staff Machine Learning Engineer (Reinforcement Learning), Motion Planning
Santa Clara, CA
- Pay
USD 130,000–220,000/year — pay source
Salary 130,000 – 220,000 USD per year Your opportunities joining PlusAI
Read the full posting- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type Full-time
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingDesign, develop, and deploy learned behavior planning models
Own the end-to-end reinforcement learning pipeline, from environment construction to training
Contribute to reinforcement learning infrastructure for large-scale distributed training
Track training, analyze model performance, and find failure modes to improve generalization
Work with simulation and planning teams to deploy models into driving pipelines
From the employer’s posting
Design, develop, and deploy learned behavior planning models using approaches such as reinforcement learning, behavior cloning, and imitation learning
Own end-to-end Reinforcement Learning pipeline from environment construction, training, and modeling.
Contribute to Reinforcement Learning Infrastructure to facilitate large-scale distributed training
Track model training, analyze model performance, identify failure modes to improve generalization across driving scenarios
Collaborate with simulation and planning teams to deploy learned behavior planning models to driving pipelines
What you’ll bring
All qualificationsCore experience
- Experience developing production code in C/C++ and Python
- Experience with machine learning frameworks such as PyTorch
- Experience with reinforcement learning
Preferred experience
- Experience with high-throughput batched driving simulators such as GPUDrive and PufferDrive
- Experience with self-play reinforcement learning
- Experience with sim-to-real in the context of robotics / autonomous driving
- Prior experience in learned behavior planning / prediction for autonomous vehicles
Qualification wording
Experience developing production code in C/C++ and Python
Experience with machine learning frameworks such as PyTorch
Experience with reinforcement learning
Experience with high-throughput batched driving simulators such as GPUDrive and PufferDrive
Experience with self-play reinforcement learning
Experience with sim-to-real in the context of robotics / autonomous driving
Prior experience in learned behavior planning / prediction for autonomous vehicles
Education & alternatives
Required skills - MS or PhD in Computer/Software Engineering, Robotics, Machine Learning or related field. - Experience developing production code in C/C++ and Python
Tools in this posting
- C
- C++
- Python
- PyTorch
Source — Tool mentions in context
- MS or PhD in Computer/Software Engineering, Robotics, Machine Learning or related field. - Experience developing production code in C/C++ and Python - Experience with machine learning frameworks such as PyTorch
- Experience developing production code in C/C++ and Python - Experience with machine learning frameworks such as PyTorch - Experience with reinforcement learning
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 2, 2026 · 58 days ago
- Recorded sightings
- 29
- Last seen by us
- Oct 31, 2026
- Employer says posted
- Aug 27, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams.
Responsibilities
- Design, develop, and deploy learned behavior planning models using approaches such as reinforcement learning, behavior cloning, and imitation learning
- Own end-to-end Reinforcement Learning pipeline from environment construction, training, and modeling.
- Contribute to Reinforcement Learning Infrastructure to facilitate large-scale distributed training
- Track model training, analyze model performance, identify failure modes to improve generalization across driving scenarios
- Collaborate with simulation and planning teams to deploy learned behavior planning models to driving pipelines
Required skills
- MS or PhD in Computer/Software Engineering, Robotics, Machine Learning or related field.
- Experience developing production code in C/C++ and Python
- Experience with machine learning frameworks such as PyTorch
- Experience with reinforcement learning
- Strong oral and written communication skills.
Preferred skills
- Experience with high-throughput batched driving simulators such as GPUDrive and PufferDrive
- Experience with self-play reinforcement learning
- Experience with sim-to-real in the context of robotics / autonomous driving
- Prior experience in learned behavior planning / prediction for autonomous vehicles
Salary
130,000 – 220,000 USD per year
Your opportunities joining PlusAI
Work, learn and grow in a highly future-oriented, innovative and dynamic field.
Wide range of opportunities for personal and professional development.
Catered free lunch, unlimited snacks and beverages.
Highly competitive salary and benefits package, including 401(k) plan.
Employment type
Full-time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Salary 130,000 – 220,000 USD per year Your opportunities joining PlusAI
- Location & working pattern
Santa Clara, CA
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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