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Senior Compiler Engineer – Rust GPU

NVIDIA2,755 open roles

Where
India, Bengaluru
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Your applicationOpen nowSenior Compiler Engineer – Rust GPUNVIDIA · India, Bengaluru

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The clock on this job

Early applications get read.

13.5% of postings close within 7 days. Measured by our own scanner across the market. NVIDIA postings stay open a median of 52 days.

Share of postings closed within
  1. 2.3%1 day
  2. 4.6%3 days
  3. 13.5%7 days
  4. 21.8%14 days
  5. 36.6%30 days
  6. 58.9%60 days
This job: posted today

NVIDIA median: 52 days open

The posting

NVIDIA is dedicated to reinvent accelerated computing. Reinvention requires great technology and amazing people. 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.

NVIDIA is hiring a Senior Compiler Engineer to join our team driving the next generation of GPU systems programming. We are redefining how developers write high-performance GPU software by bringing the safety, expressiveness, and modern tooling of Rust to native GPU and CUDA development. On this team, you will build cutting-edge compiler pipelines, custom intermediate representation (IR) frameworks, and JIT compilation systems that bridge host and device execution—allowing developers to write memory-safe, high-performance GPU kernels in idiomatic Rust.

What you’ll be doing:

  • Develop Rust-to-GPU Compiler Pipelines: Design, implement, and maintain custom compiler backends (such as rustc codegen backends and proc-macros) and Rust-native intermediate representation (IR) frameworks to compile standard Rust directly to high-performance CUDA PTX and machine code.
  • Build compiler IRs and Optimizers: Work with modern compiler architectures to lower Rust AST and MIR into IRs including MLIR, PTX, and LLVM, including GPU-specific optimizations.
  • Support complex ahead-of-time, just-in-time, and link time optimization workflows: Build state-of-the-art tooling to support users targeting a broad family of NVIDIA GPUs, host platforms, and feature sets.
  • Define Safe Parallel Abstractions: Architect innovative compiler-enforced safety models that extend Rust's ownership, borrowing, and lifetime disciplines across the GPU launch boundary—preventing data races and enforcing memory safety during asynchronous GPU execution.
  • Expose Next-Gen Hardware Features: Implement type-safe, ergonomic device-side abstractions in Rust for low-level GPU hardware primitives, including shared memory, barriers, scoped atomics, Tensor Memory Accelerator (TMA), and warp/cluster-level operations.
  • Build the future: Supporting today’s accelerated computing applications is not sufficient. We have to build composable building blocks for others around us to build the applications of tomorrow.

What we need to see:

  • Bachelor's, Master's, or Ph.D. in Computer Science, Computer Engineering, a related field, or equivalent experience.
  • 5+ years of relevant work or research experience in compiler development, language design, or GPU code generation.
  • Deep expertise in the Rust programming language, including a strong grasp of compiler internals (rustc), Rust MIR, procedural macros, and Rust's borrow-checker/lifetime model.
  • Hands-on experience with compiler infrastructures, intermediate representations (IRs), and code generation (such as LLVM IR, MLIR, or custom IR systems).
  • Solid understanding of parallel programming models, GPU architectures, and CUDA programming.
  • Strong software design skills, including debugging, profiling, and benchmarking compilers and GPU kernels.
  • Ability to orchestrate agents for product requirement design, architecture, code development, testing, code review, and issue triage.
  • Ability to work independently, define project goals and scope, and drive complex compiler-engineering efforts from research to production.

Ways to stand out from the crowd:

  • A track record of contributing to the Rust compiler (rustc), Cargo tooling, or open-source Rust-to-GPU projects.
  • Experience building custom compiler front-ends, AST translators, or JIT engines.
  • Familiarity with MLIR or other extensible compiler frameworks.
  • Deep proficiency in low-level GPU programming, including the use of modern hardware features (e.g., Tensor Cores, warp-level shuffles, or asynchronous transfer pipelines).
  • Experience designing Domain-Specific Languages (DSLs) or tile-based programming abstractions for tensor processing.

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 programming languages and systems technology, we want to hear from you.

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