- A MS, or PhD (or equivalent experience) in Computer Science, Electrical Engineering, Computer Engineering, or a related field, with 12+ years of relevant work or research experience.
- Demonstrated principal-level technical impact in one or more of the following areas: large-scale AI training systems, GPU performance optimization, distributed systems, high-performance computing, ML frameworks, compilers/runtimes, or hardware/software co-design.
- Deep hands-on experience analyzing and optimizing performance of large-scale deep learning workloads, especially transformer-based models, LLM pre-training, reinforcement learning, fine-tuning, or other post-training workloads.
- Strong understanding of GPU and AI accelerator architecture from individual accelerators to datacenter-scale systems.
- Experience with distributed training techniques such as data parallelism, tensor parallelism, pipeline parallelism, expert parallelism, sequence parallelism, activation checkpointing, mixed precision training, and communication/computation overlap.
- A strong track record of using profiling, tracing, benchmarking, and performance modeling tools to diagnose complex bottlenecks and drive measurable improvements.
- Excellent communication and technical leadership skills, with the ability to influence architecture and software decisions across multiple teams without relying on direct authority.
GPU computing is the most productive and pervasive platform for deep learning and AI. It begins with the most advanced GPUs and the systems and software we build on top of them. We integrate and optimize every deep learning framework. We work with the major systems companies and every major cloud service provider to make GPUs available in data centers and in the cloud. We craft computers and software to bring AI to edge devices, such as self-driving cars and autonomous robots. AI has the potential to spur a wave of social progress unmatched since the industrial revolution.
This opportunity offers you the ability to collaborate with some of the most forward-thinking and hard-working people in the world, shaping the future of AI in a creative and autonomous work environment that encourages innovation. If you're passionate about working across the full hardware & software stack—from GPU architecture to application code—to achieve optimal performance, we want to hear from you!
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.