Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Python @ 7
Algorithms @ 4
Machine Learning @ 4
LLM @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
At NVIDIA, we are seeking exceptional engineers to join our autonomous driving team to design, implement, and deploy cutting-edge end-to-end autonomous driving systems running on NVIDIA chips in mass-production vehicles. The team is evolving from AI 1.0 (building a driver from scratch) to AI 2.0 (teaching an intelligent agent to drive) and leverages LLMs, VLMs, and VLAs to bring improved reasoning, planning, and interactivity to autonomous vehicles and robotics.
Responsibilities
- Design and train large-scale models (including generative, imitation, and reinforcement learning) to improve planning and reasoning capabilities of driving systems.
- Build, pre-train, and fine-tune LLM / VLM / VLA systems for deployment in real-world autonomous driving and robotics applications.
- Explore novel data generation and collection strategies to improve diversity and quality of training datasets.
- Collaborate with cross-functional teams to deploy AI models in production environments while ensuring performance, safety, and reliability.
- Integrate machine learning models directly with vehicle firmware to deliver production-quality, safety-critical software.
Requirements
- Hands-on experience building LLMs, VLMs, or VLAs from scratch OR a proven track record as a top-tier coder passionate about autonomous systems.
- Deep understanding of modern deep learning architectures and optimization techniques.
- Proven record of deploying production-grade ML models for self-driving, robotics, or related fields at scale.
- Strong programming skills in Python and proficiency with major deep learning frameworks.
- Familiarity with C++ for model deployment and integration in safety-critical systems.
- Master’s degree or PhD (or equivalent experience).
- 8+ years of work experience in autonomous vehicles (AV) or related field.
Ways to Stand Out (Preferred / Nice-to-have)
- Experience with LLM/VLM/VLA systems deployable to autonomous vehicles or general robotics.
- Publications, open-source contributions, or competition wins related to LLM/VLM/VLA systems.
- Deep understanding of behavior and motion planning in real-world AV applications.
- Experience building and training large-scale datasets and models.
- Proven ability to optimize algorithms for real-time performance in resource-constrained environments and take projects from concept to production.
Compensation & Benefits
- Base salary ranges (depending on level and location):
- Level 4: 184,000 USD - 287,500 USD
- Level 5: 224,000 USD - 356,500 USD
- You will also be eligible for equity and benefits.
Other Details
- Employment type: Full time
- Location: Santa Clara, CA, United States
- Applications for this job will be accepted at least until January 27, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.