Senior Deep Learning Engineering - Autonomous Vehicles

Details

NVIDIA is building the future of autonomous driving—from the silicon to the full-stack AI systems that power next-generation robots on wheels. This role focuses on data and intelligence extraction from petascale fleets. You will work hands-on training and deploying Large Language Models (LLMs) and Vision-Language Models (VLMs) in production environments, collaborating with other researchers and software engineers to take pioneering AI models from prototype to production.

Responsibilities

• Explore SOTA LLM/VLM models for search and classification of AV scenarios
• Hands-on model developments such as fine-tuning large LLM/VLMs for internal use cases
• Collaborate with software engineers and researchers to ensure seamless integration of models from training to deployment

Requirements

• Master’s or PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent experience)
• 10+ years of professional experience in deep learning or applied machine learning
• Strong foundation in deep learning algorithms, including hands-on experience with LLMs and VLMs
• Deep understanding of general transformer architectures, inference bottlenecks, and popular model architectures such Qwen family
• Proficient in building and deploying models using PyTorch in production-grade environments
• Solid programming skills in Python

Ways to stand out from the crowd

• Proven experience deploying LLMs or VLMs at scale in real-world applications using vLLM, SGLang
• Hands-on experience with SFT, DPO, GRPO techniques for fine-tuning
• Proven experience in developing image and video search solutions at scale