Senior Deep Learning Engineering - Autonomous Vehicles

Senior Deep Learning Engineering - Autonomous Vehicles

NVIDIA - 4.2

Santa Clara, CA Job Details Full-time $224,000 - $356,500 a year 1 day ago Qualifications Computer Science PyTorch Software deployment Master's degree Doctoral degree in Computer Science Doctor of Philosophy Model deployment Doctoral degree in computer engineering Computer Engineering Scalability Master's degree in electrical engineering Model training Master's degree in computer science Machine learning libraries Master's degree in computer engineering Senior level Electrical Engineering AI Machine learning frameworks Doctoral degree in electrical engineering Prototypes 10 years Full Job Description NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology—and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. At NVIDIA, we're building the future of autonomous driving — from the silicon to the full-stack AI systems that power next-generation robots on wheels. Our ability to deliver safe, scalable autonomy depends on one thing above all: Data. Extensive, diverse, high-quality data. We are seeking a highly skilled Deep Learning Engineer to develop systems and algorithms extracting intelligence from petascale fleets. This role offers an opportunity to build the data engine powering one of the world's most advanced AI platforms. We are looking for hands-on experience training and deploying Large Language Models (LLMs) and Vision-Language Models (VLMs) in production environments. You will collaborate with other researchers, software engineers to bring pioneering AI models from prototype to production.

What you will be doing:

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.

What we want to see:

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. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until May 18, 2026. 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.