
location_onSan Joaquin County, California, United States
NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years! It's an outstanding legacy of innovation that's fueled by phenomenal technology—and outstanding people! As part of NVIDIA's applied LLM and AI chip design team, you will have the opportunity to tap into the unlimited potential of AI and change the landscape of chip design at NVIDIA and throughout the industry. Our team operates at the intersection of research, engineering, and product development, transforming innovative ideas and research breakthroughs into real-world solutions. If you're passionate about the latest research and cutting-edge technologies shaping generative AI, this role and team offer an exciting opportunity to be at the forefront of innovation.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous engineer who loves a challenge? Come join our applied AI engineering team and help us build the future of chip design.
This posting is for an existing vacancy. Applications for this job will be accepted at least until June 2, 2026. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.
Work model: Hybrid
San Joaquin County, California, United States
California
Skills: Python, Machine Learning, Ai, LLM, Rag Pipelines, Vector Databases, Multi-Agent Systems, Fine Tuning.
Education: Master's in Electrical Engineering or equivalent experience; PhD in Electrical Engineering or equivalent experience; Master's in Computer Science or equivalent experience; PhD in Computer Science or equivalent experience.