Senior Deep Learning Compiler Engineer (XLA) – Equity

NVIDIA; Redmond (WA); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA in Redmond seeks versatile software engineers for the XLA team to build high-performance, production-grade software at the core of next-generation AI systems. You will work on compiler optimization, graph partitioning, and code generation for NVIDIA GPUs, collaborating with hardware teams and contributing to JAX-related features.

Required are strong C/C++ skills, advanced education, and 4+ years in performance analysis or compiler work. Experience with XLA/MLIR/LLVM/Triton is a plus.

Qualifications

• : Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field (or equivalent experience).
• : 4+ years of relevant work or research experience in performance analysis and compiler optimizations.
• : Ability to work independently, define project goals and scope, and lead your own development effort adopting clean software engineering and testing practices.
• : Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.
• : Strong foundation in architecture of CPU, GPUs or other high performance hardware accelerators. Knowledge of high-performance computing and distributed programming.
• : CUDA or OpenCL programming experience is desired but not required.
• : Experience with the following technologies is a huge plus: XLA, TVM, MLIR, LLVM, OpenAI Triton, deep learning models and algorithms, and deep learning framework design.
• : Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team. A history of mentoring junior engineers and interns is a bonus.

Responsibilities

• Crafting and implementing compiler optimization techniques for deep learning network graphs.
• Designing novel graph partitioning and tensor sharding techniques for distributed training and inference.
• Performance tuning and analysis.
• Code-generation for NVIDIA GPU backends using open-source compilers such as MLIR, LLVM and OpenAI Triton.
• Designing user facing features in JAX and related libraries and other general software engineering work.
• Working closely with GPU hardware engineering teams to design AI compiler software features for next-generation GPUs.

Skills

C/C++ programming

performance analysis

compiler optimizations

distributed programming

GPU/CPU architecture

CUDA or OpenCL

XLA

TVM

MLIR

LLVM

OpenAI Triton

deep learning models

deep learning framework design

Education

Bachelor's/Master's/Ph.D. in Computer Science or related field

Tools

MLIR

LLVM

OpenAI Triton

CUDA

OpenCL

Job description

NVIDIA in Redmond seeks versatile software engineers for the XLA team to build high-performance, production-grade software at the core of next-generation AI systems. You will work on compiler optimization, graph partitioning, and code generation for NVIDIA GPUs, collaborating with hardware teams and contributing to JAX-related features.

Required are strong C/C++ skills, advanced education, and 4+ years in performance analysis or compiler work. Experience with XLA/MLIR/LLVM/Triton is a plus.