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NVIDIA

Designs the chips and software that power AI

Senior Compiler Engineer - Agentic Compiler Systems

Full-TimePosted on 10/19/2026Deadline 10/23/26
$152k - $241.5k+ Equity
Senior
Bachelor's, Master's, PhD
Oregon, USA+5 moreMore locations: California, USA | Austin, TX, USA | Texas, USA | Redmond, WA, USA | Santa Clara, CA, USA
Hybrid
Software EngineeringSystems Software Engineering
Company Historically Provides H1B Sponsorship

About the job

Requirements
  • A bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent experience.
  • At least 5 years of relevant industry or academic experience in compilers, AI systems, numerical computing, verification, high-performance computing, or related areas.
  • Hands-on experience in compiler implementation, program analysis, code generation, optimization, low-level performance engineering, or correctness infrastructure.
  • Experience in one or more of agent systems, coding agents, compiler automation, numerical analysis, program verification, differential testing, or formal or semi-formal validation methods.
  • Strong C/C++ and Python programming skills, with solid software engineering fundamentals.
  • Experience with GPU programming and performance optimization using CUDA or comparable accelerator platforms.
  • Ability to work across system boundaries, from model-driven workflows and compiler infrastructure to runtime and hardware-aware optimization.
Responsibilities
  • Design, build, and optimize intelligent low-level compiler systems, including compiler-oriented agents, multi-step transformation workflows, tool use, memory, and orchestration.
  • Develop systems that reason about low-level intermediate representations, code generation, optimization passes, scheduling, numerical precision, and performance tradeoffs across GPU-centric workloads.
  • Build the data, environments, verification, reward, and evaluation systems needed to continuously improve compiler quality, numerical correctness, robustness, and performance.
  • Develop infrastructure for numerical validation, differential testing, regression detection, and correctness verification for generated or transformed code.
  • Co-design compiler and verification workflows across the software stack, spanning models and inference, compiler pipelines, runtimes, libraries, kernels, and GPUs.
  • Collaborate with internal compiler, CUDA, library, runtime, and hardware teams to integrate compiler, agentic, and verification capabilities into products.
  • Drive performance analysis and optimization for generated or transformed code, focusing on correctness, scalability, and real-world deployment.
Desired Qualifications
  • A master's or PhD degree.
  • Experience with Rust.
  • A track record of building high-impact compiler infrastructure, coding agents, verification frameworks, correctness tooling, or developer tools.
  • Deep expertise in low-level compiler stacks such as LLVM, MLIR, PTX, Triton, or other intermediate representation or code-generation frameworks.
  • Experience building or optimizing AI-assisted compilation, numerical validation systems, equivalence checking, autotuning, or compiler verification workflows.
  • Deep expertise in GPU systems, numerical behavior, and performance optimization, demonstrated through benchmark results, deployed systems, publications, or widely used software.
  • Publications or open-source leadership in compilers, numerical computing, verification, formal methods, agentic AI, high-performance computing, AI systems, or programming systems.

About the company

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • AI demand is still surging: data center sales rose 117% to $89 billion in the quarter ending July 2026.
  • Stock grants are worth more: shares hit a record in October 2026, up 28% for the year.
  • Engineering dominates hiring: 1,722 of NVIDIA's 2,686 job listings in October 2026 were in engineering.

What critics are saying

  • Big buyers are hedging: Meta's February 2026 agreement covers 6 gigawatts of AMD chips.
  • Financing its buyers is getting harder: lenders pushed back on NVIDIA's $500 billion chip-backed loan plan in October 2026.
  • Staff described long hours: Bloomberg's August 2024 interviews reported seven-day weeks, late nights and shouting matches.

What makes NVIDIA unique

  • Rivals must match its software too: over 7.5 million developers use CUDA and other NVIDIA tools to program its chips.
  • The CEO has a broad direct staff: Jensen Huang says over 60 people report to him, without one-on-ones.
  • People rarely leave: NVIDIA's yearly staff turnover is 3.7%, versus a 21.9% average across the tech industry.

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Benefits

  • Company Equity
  • 401(k) Company Match

Growth & Insights and Company News

6 month growth

1%

1 year growth

0%

2 year growth

-1%
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