Senior Compiler Engineer, AI Inference Platforms

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI – the next era of computing – with the GPU acting as the brain of computers, robots, and self-driving cars that perceive and understand the world. Today, we are increasingly known as “the AI computing company.”

We are looking for an AI & Deep Learning Compiler Engineer to join the Deep Learning & AI Compiler (DLC) team. Academic and commercial groups worldwide use GPUs to power a revolution in deep learning, enabling breakthroughs in large language models, generative AI, recommendation systems, image classification, speech recognition, and more. The DLC is the backbone of NVIDIA’s inference engine across data centers, personal devices, automotive, and robotics.

The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in both ahead‑of‑time and just‑in‑time forms.

• Analyzing deep learning networks and developing compiler optimization algorithms.
• Collaborating with deep learning software framework teams and GPU architecture teams to accelerate the next generation of deep learning software.
• Defining public APIs, performance optimizations, and analysis; crafting and implementing compiler techniques for AI workloads and future NVIDIA GPUs.

• Bachelor’s, Master’s or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience.
• 3+ years of relevant work or research experience in performance analysis and compiler optimizations.
• Experience with compiler technologies (e.g., MLIR, LLVM, XLA, Triton, etc.).
• Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design.
• Ability to work independently, define project goals and scope, and lead your own development efforts.
• Strong interpersonal skills in a dynamic product‑oriented team.

• Proficiency in CPU and/or GPU architecture; CUDA or OpenCL programming experience.
• Understanding of deep learning models, algorithms, and frameworks such as PyTorch and JAX.
• GPU kernel authoring and performance analysis using tools such as Nsight Compute.
• Track record of mentoring early‑career engineers and interns.
• Experience with new hardware bring‑up.

Base salary: $152,000 – $241,500 USD, depending on location, experience, and comparable positions. Eligible for equity and a generous benefits package.

NVIDIA is committed to fostering a diverse work environment and is a proud equal‑opportunity employer. We do not discriminate 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.