Deep Learning Compiler Verification Engineer

NVIDIA is hiring a Deep Learning Compiler Verification Engineer in Santa Clara, United States. It pays $116k-$190k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
Tools and skills the posting cites include PyTorch and JAX.
Level classifies it as a mid-level role.
Level lists 1,800+ other open roles at NVIDIA.
The role was posted in the last few days.

AI in this role

pytorchjax

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.

We are building the next generation of compiler technologies to accelerate deep learning workloads. We are looking for an engineer to implement compiler verification software & related infrastructure in the AI space. You will be solving critical problems working alongside a diverse set of minds in GPU computing and systems software, doing what you enjoy. If this sounds like a fun challenge, we want to hear from you.

What you'll be doing:

Develop and maintain components of systems to reason about correctness in deep learning compilers, across graph transformations, IR lowering, and GPU execution.
Work with deep learning compiler and architecture teams to analyze and validate optimizations (e.g., graph rewrites in MLIR, fusion passes, mixed-precision transformations), ensuring they preserve semantics and numerical behavior.
Implement and extend test generation systems that use deep learning solutions and analysis methods to drive in-depth testing. These systems explore the vast combinatorial space of model topologies, precision modes, and hardware targets.
Contribute to improving how we measure functional quality and performance as models, compiler stacks, and hardware continue to evolve.

What we need to see:

BS, MS or PhD in Computer Science, Computer Engineering, Mathematics, or equivalent experience.
2+ years of hands-on software engineering experience, with experience in compiler development, deep learning systems, or compiler verification.
Proficiency in Python or C++ and experience with one major DL framework. This could be PyTorch, JAX/XLA, TensorRT, or a similar framework. Experience should involve model execution, graph representation, or runtime behavior.
Strong problem-solving and debugging skills — ability to reason about model behavior and compiler-generated code, investigate correctness issues, and collaborate with teammates to resolve edge-case failures.

Ways to stand out from the crowd:

Experience with compiler technologies such as LLVM, MLIR, TVM, or XLA, and familiarity with compiler passes, IR semantics, or correctness testing.
Exposure to formal methods or language specification: type systems, program semantics, or proof-based verification.
Experience with DL model internals such as quantization, operator fusion, mixed-precision, or graph-level optimization.

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 116,000 USD – 189,750 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 4, 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

Deep Learning Compiler Verification Engineer at NVIDIA rates 86 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

Deep Learning Compiler Verification Engineer is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $116k-$190k a year.
The role is based in US, CA, Santa Clara.
The job was posted on October 31, 2026.
Seniority: mid.
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

PyTorchJAX

Questions you could be asked

What's a project where you used PyTorch hands-on?
Walk me through how you've used JAX in your day-to-day work.
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: 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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