NVIDIA's GPUs are at the core of modern AI infrastructure, from training large-scale models to running inference in production. That position depends on software as much as hardware, and compiler engineering is a big part of what makes it work.
We're hiring senior software engineers for a compiler team within NVIDIA's deep learning software organization. This team builds a code generation backend that connects frontend ML compilers to NVIDIA's GPU compilation and execution stack, targeting high-performance kernel generation for deep learning workloads.
What you'll be doing:
You'll work on the compiler infrastructure responsible for generating high-performance GPU kernels from frontend compiler representations. This spans the full codegen pipeline: taking in high-level graph operations, lowering them through intermediate representations, and producing efficient code targeting NVIDIA's GPU compiler backends. You may work at any layer of this stack, from the interface with compiler frontends down to the tile-level IR and code generation machinery underneath.
Designing and implementing compiler passes, IRs, and lowering pipelines for GPU kernel generation for DL compiler and framework integration.
Building MLIR-based transformations and compiler infrastructure connecting frontend representations to backend code generation.
Working within and contributing to the backend compilation stack itself, including tile-based IRs and their associated optimization and lowering infrastructure.
Performance analysis and optimization across the codegen pipeline, targeting both compute-bound and memory-bound GPU kernels against competitive baselines.
Making architectural decisions about how the codegen backend integrates with compiler frontends, GPU libraries, and NVIDIA's broader compilation ecosystem.
Setting technical direction for your area: scoping multi-quarter work, defining abstractions that hold up as the stack evolves, and influencing roadmap priorities.
Collaborating across teams, including hardware architects, framework teams, library teams, and external partners.
What we need to see:
BS, MS, or PhD in Computer Science, Computer Engineering, or a related field (or equivalent experience).
6+ years of relevant work or research experience in compilers, with focus on code generation, IR design, or optimization passes.
Strong C/C++ skills, including debugging, performance profiling, and designing for maintainability.
Ability to work independently and drive projects with increasing scope and ambiguity.
Strong interpersonal and communication skills, including the ability to work across teams and with external partners.
Ways to stand out from the crowd:
Hands-on MLIR experience: designing dialects, writing passes, and reasoning about abstraction boundaries in a compilation pipeline.
Track record of owning and delivering complex compiler infrastructure end to end.
Working experience with GPU or other high-performance accelerator architectures and execution models.
Contributions to open-source compiler projects (MLIR, LLVM, XLA, TVM, OAI Triton).
History of mentoring engineers and raising the technical bar on a team.
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 program manager with a real passion for technology, we want to hear from you.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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.Top Skills
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.”
