英伟达Senior Prediction and Planning Engineer, VLM - Autonomous Vehicles
任职要求
Join our team at NVIDIA to develop brand new, end-to-end autonomous driving systems for 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 outstanding 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 Want 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. • BS/MS in Computer Science or equivalent experience. • 8+ years of experience in the field or meaningful experience • 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. 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. • Proven ability to optimize algorithms for real-time performance in resource-constrained environments. Strong track record of taking projects from concept to production deployment.
工作职责
N/A
• Develop and Manage Supplier Quality Systems: Establish and maintain comprehensive quality control plans, inspection methodologies, documentation (QMS, IQC/IPQC/OQC), and measurement system validations (MSA, GR&R, FAI/CpK) from development through mass production. • Lead Proactive Risk Mitigation: Conduct supplier process and product audits to identify potential risks. Implement preventive measures, training programs, and align specifications (MSOP, limit samples for cosmetic and color standards) to prevent defects. • Drive Root Cause Analysis and Correction: Lead meticulous problem-solving for quality issues using 8D, 5Whys, and DOE to find root causes and implement effective, validated corrective and preventive actions. • Oversee Product Reliability and Validation: Handle Ongoing Reliability Testing (ORT), supervise failure analysis, and validate key assembly processes to ensure long-term product performance and quality. • Prevent Defect Leakage: Implement and lead Out-of-Box Audit (OBA) processes at suppliers to catch cosmetic and functional issues before products are shipped to the factory (FATP). • Facilitate Cross-Functional Collaboration: Act as the primary quality liaison between suppliers and internal teams (e.g., FATP team, engineering team) to drive improvements and ensure a smooth new product introduction (NPI) and mass production (MP) process. • Monitor and Communicate Quality Performance: Track key quality metrics, run major issue lists (MIL), and provide regular yield summary updates to stakeholders on supplier performance and improvement initiatives. • Develop and implement supplier training programs: Create operator training plans and production line qualification plans.