Role at a glance
- Salary
- $184K – $356.5K/yr
- Location
- 2 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Education
- PhD
Spotted an issue?
We’ll check it against the original posting.
Role Summary
This role joins NVIDIA’s autonomous driving team to design, implement, and deploy end-to-end autonomous driving systems on NVIDIA chips in mass-production vehicles. The work focuses on applying LLMs, VLMs, and VLAs to improve reasoning, planning, and interactivity in autonomous vehicles and robotics.
What You'll Do
- Design and train large-scale generative, imitation, and reinforcement learning models to improve driving-system planning and reasoning...
- Build, pre-train, and fine-tune LLM, VLM, and VLA systems for autonomous driving and robotics applications
- Explore data generation and collection strategies to improve training-dataset diversity and quality
- Collaborate with cross-functional teams to deploy AI models in production environments
- Integrate machine learning models with vehicle firmware for production-quality, safety-critical software
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
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 Python programming skills and proficiency with major deep learning frameworks; familiarity with C++ for model deployment and integration in safety-critical systems.
Required
- Hands-on experience building LLMs, VLMs, or VLAs from scratch or a proven track record as a top-tier coder passionate about autonomous...
- 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
- PhD with 4+ years, MS (or equivalent experience) with 6+ years of relevant experience in Computer Science, Computer Engineering, or a...
Preferred
- 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 strong track record of taking...
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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. Our strategy has evolved from AI 1.0 — building a driver from scratch — to AI 2.0 — teaching an intelligent agent to drive. This next phase leverages LLMs, VLMs, and VLAs to bring unprecedented reasoning, planning capabilities, and interactivity with the driving system to autonomous vehicles and general robotics. Let’s build the future of autonomy—together!
What You’ll Be Doing:
Design and train innovative large-scale models—including generative, imitation, and reinforcement learning—to improve the planning and reasoning capabilities of our 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, ensuring performance, safety, and reliability standards are met.
Integrate machine learning models directly with vehicle firmware to deliver production-quality, safety-critical software.
What We Need to See:
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.
PhD with 4+ years, MS (or equivalent experience) with 6+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
Ways to Stand Out from the Crowd:
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 strong track record of taking projects from concept to production deployment.
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.#deeplearningAbout 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.