Senior Software Engineer - Compilers and Applied AI

NVIDIA•Redmond, WA

About The Position

NVIDIA has been a leader in computer graphics, PC gaming, and accelerated computing for over 25 years, driven by innovation and talented individuals. The company is now leveraging AI to define the next era of computing, with GPUs acting as the brains for computers, robots, and self-driving cars that can understand the world. This role is part of a team that builds solutions to optimize all layers of the CUDA ecosystem, aiming for class-leading speedups in modern high-performance workloads and models. The Senior Software Engineer will architect and implement highly scalable solutions for various use-cases, develop new innovative workflows, and work on compiler- or runtime-driven solutions to accelerate critical workloads, generate optimal code patterns, and address high-impact AI challenges. The position involves close collaboration with internal NVIDIA software and hardware teams to integrate the latest developments into NVIDIA products.

Requirements

Bachelor ’s degree in Computer Science, Electrical Engineering, or related field (or equivalent experience)
6+ years of industry or academia experience with software engineering, compilers and developer tools; exposure to building comprehensive optimization frameworks, and hands-on experience with product environments
Strong knowledge of compilers, code generation, and GPU architecture
Experience with GPU programming and performance optimization (CUDA or equivalent)
Extensive Python programming skills, along with software engineering fundamentals
Basic programming skills in other languages such as C/C++, Racket and Rust
Strong mathematical and scientific foundation relevant to optimization heuristics/algorithms, ML and data science
Track record developing and productizing software, optimization frameworks and/or developer tooling

Nice To Haves

Familiarity with genetic/evolutionary algorithms, predictive modeling, and complex systems
Deep expertise in GPU performance optimizations, evidenced by benchmark wins or published results
Hands-on experience building compilers or compiler components using the LLVM framework, including optimization passes and code generation
Familiarity with NVIDIA and open source compilers like LLVM, MLIR, PTX and OpenAI Triton
Experience with Data Science projects, specifically with MLOPS workflows and tools, like W&B, MLflow, etc.

Responsibilities

Design and build high-performance optimization frameworks for the entire CUDA ecosystem
Co-design novel solutions with software, hardware and algorithm teams; influence and adopt new capabilities as they become available
Develop reproducible, high-fidelity evaluation frameworks covering performance, quality and developer productivity
Collaborate across the AI stack — from hardware through compilers/toolchains, kernels/libraries, frameworks, distributed training, and inference/serving