Senior Compiler Engineer, AI Inference Platforms

NVIDIA is hiring a Senior Compiler Engineer, AI Inference Platforms in Santa Clara, United States. It pays $152k-$242k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include PyTorch, JAX and speech.
Level classifies it as a senior role.
Level lists 2,700+ other open roles at NVIDIA.

AI in this role

PyTorchJAX

speech

NVIDIA's invention of the GPU 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, we are increasingly known as “the AI computing company”.

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.
Collaborating with members of the deep learning software framework teams and the GPU architecture teams to accelerate the next generation of deep learning software.
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. CUDA or OpenCL programming experience.
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 competitive salaries and a generous benefits package, we are 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 and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, 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 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 November 3, 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.

How we rate this

Senior Compiler Engineer, AI Inference Platforms at NVIDIA rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Compiler Engineer, AI Inference Platforms is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $152k-$242k a year.
The role is based in US, CA, Santa Clara.
The job was posted on February 23, 2026.
Seniority: senior.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

SpeechPyTorchJAX

Questions you could be asked

What have you built with speech recognition or text-to-speech, and where did it break?
Walk me through how you've used PyTorch in your day-to-day work.
What are the limits of JAX that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Speech, PyTorch, and JAX. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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