3 days ago
Bengaluru, IndiaSenior
Responsibilities
- Develop and maintain Rust-to-GPU compiler pipelines, including rustc codegen backends and procedural macros, targeting CUDA PTX and machine code.
- Build compiler intermediate representations and optimizers that lower Rust AST and MIR into MLIR, PTX, LLVM, and custom IRs.
- Develop ahead-of-time, just-in-time, and link-time optimization workflows for NVIDIA GPUs, host platforms, and feature sets.
- Design compiler-enforced safety models extending Rust ownership, borrowing, and lifetime disciplines across GPU launch boundaries.
- Implement Rust abstractions for GPU hardware features including shared memory, barriers, scoped atomics, Tensor Memory Accelerator, and warp- or cluster-level operations.
- Debug, profile, benchmark, and drive complex compiler-engineering efforts from research through production.
Requirements
- 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 Rust, including rustc internals, Rust MIR, procedural macros, and the borrow-checker and lifetime model.
- Hands-on experience with compiler infrastructures, intermediate representations, and code generation such as LLVM IR, MLIR, or custom IR systems.
- Understanding of parallel programming models, GPU architectures, and CUDA programming.
- Strong software design, debugging, profiling, and compiler and GPU-kernel benchmarking skills.
- Ability to orchestrate agents for product requirements, architecture, development, testing, code review, and issue triage.
- Ability to work independently, define project goals and scope, and lead complex compiler-engineering efforts.
- Preferred experience contributing to rustc, Cargo tooling, or open-source Rust-to-GPU projects; building compiler front ends, AST translators, or JIT engines; using extensible compiler frameworks; programming low-level GPU features; or designing DSLs and tile-based tensor abstractions.
Benefits
- Competitive salary and generous benefits package.
- NVIDIA describes the role as part of rapidly growing engineering teams in a supportive and collaborative work environment.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.