What we need to see: M.Sc. or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience. +5 years of experience. Strong ML/Data Science background with hands-on experience in LLMs or generative AI. A systems-level mindset with the ability to estimate end-to-end requirements across the entire AI stack. Proven ability to translate research and product requirements into clear software/hardware specifications. Exceptional research skills: you can digest academic papers, self-learn new domains, and independently test hypotheses. Advanced Python programming skills for performance modeling and data analysis. Excellent communication skills, with the ability to present complex findings with clarity and conviction. A pragmatic approach: you are detail-oriented but can prioritize effectively to focus on the most critical issues. Ways to Stand Out from the Crowd: Deep understanding of datacenter infrastructure, network topologies, and protocols. Expertise in distributed training methods and their impact on infrastructure. Knowledge of AI performance metrics and the impact of different deployment strategies. Experience extrapolating academic research into tangible hardware architecture requirements. A track record of leading complex, multidisciplinary research projects that result in production impact. NVIDIA has some of the most forward-thinking and talented people in the world working for us. If you're an autonomous researcher passionate about connecting AI applications with the infrastructure that powers them, we want to hear from you.
