[Remote] Deep Learning Senior Engineer, End-To-End Autonomous Driving
Note: The job is a remote job and is open to candidates in USA. NVIDIA is seeking exceptional engineers to join their autonomous driving team to design, implement, and deploy cutting-edge end-to-end autonomous driving systems. The role involves training innovative large-scale models and collaborating with cross-functional teams to ensure the deployment of AI models in production environments.
Responsibilities
- 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
Skills
- 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
- 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
Benefits
- You will also be eligible for equity and benefits.
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