Senior AI Compiler Engineer, Algorithms and Code-Generation

Posted 22 Days Ago
5 Locations
In-Office or Remote
152K-242K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Develop and implement compiler optimization algorithms for deep learning workloads, analyze networks, debug and profile GPU performance (CUDA), define public APIs, and deliver ahead-of-time and just-in-time compilation techniques for NVIDIA GPUs to improve inference performance, build times, and memory efficiency.
Summary Generated by Built In

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.

We are looking for an AI & Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning & AI Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AI, recommendation systems, image classification, speech recognition, etc. With the rapid advancement of AI, our DLC has been the backbone of NVIDIA’s inference engine, spanning 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 the forms of both Ahead-of-Time and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community.

What you'll be doing:

  • Analyzing deep learning networks and developing compiler optimization algorithms.

  • Strong programming skills in CUDA including analyzing and debugging performance bottlenecks on GPUs

  • Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler techniques for AI workloads and future NVIDIA GPUs.

What we need to see:

  • 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 are required along with the ability to work in a dynamic product-oriented team.

Ways to stand out from the crowd:

  • Proficient in CPU and/or GPU architecture especially modern Nvidia GPUs like Hopper and Blackwell

  • Understanding of deep learning models, algorithms, and frameworks, such as PyTorch, JAX.

  • GPU kernel authoring and performance analysis using tools such as Nsight Compute.

  • A track record of success in mentoring early-career engineers and interns is a bonus.

  • Track record on new hardware bring-up is a plus.

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 18, 2026.

This posting is for an existing vacancy. 

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.

Skills Required

  • 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)
  • Strong programming skills in CUDA, including analyzing and debugging GPU performance bottlenecks
  • 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 development efforts
  • Strong interpersonal skills and ability to work in a dynamic product-oriented team
  • Proficiency in CPU and/or GPU architecture, especially modern NVIDIA GPUs like Hopper and Blackwell
  • Understanding of deep learning models and frameworks such as PyTorch and JAX
  • GPU kernel authoring and performance analysis using tools such as Nsight Compute
  • Track record mentoring early-career engineers and interns
  • Experience with new hardware bring-up

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

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 can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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