Technical Leader/Manager, GPU Software

It looks like you’ve posted the full NVIDIA GPU‑Backend Compiler Manager job description.
If you’re planning to apply, I can help you put together a strong application package (resume, cover‑letter, LinkedIn profile tweaks) and even prep you for the interview rounds.

Below are a few ways we can move forward—just let me know which one (or any combination) you’d like to focus on:

What you might need	How I can help
Tailored résumé	• Re‑format your experience to match the “What You Will Be Doing” and “What We Need To See” sections. • Highlight the 6+ years of production‑compiler work, 3+ years of leadership, and any LLVM/MLIR projects. • Add quantifiable impact (e.g., “Reduced GPU kernel compile time by 30 % across 5 product lines”).
Cover‑letter	• Draft a concise, 3‑paragraph letter that ties your background to NVIDIA’s mission (AI‑computing, GPU‑centric). • Showcase specific stories of mentoring distributed teams, delivering JIT‑compiler features, and collaborating across graphics/CUDA groups. • End with a clear call‑to‑action and enthusiasm for the “AI computing company” vision.
LinkedIn / online profile	• Optimize headline (“Senior Compiler Engineer & Technical Lead – LLVM/MLIR, GPU JIT”). • Write a summary that mirrors the language of the posting (parallel programming, performance analysis, cross‑org influence).
Interview preparation	• Technical deep‑dive: common NVIDIA compiler questions (LLVM passes, code‑gen for SM architecture, JIT vs. AOT trade‑offs). • Leadership scenarios: coaching distributed engineers, handling conflicting priorities, driving cross‑team alignment. • Behavioral “STAR” stories aligned with the job’s key competencies.
Salary & negotiation tips	• Benchmark the $224 k–$356 k range for your location and experience. • Draft a negotiation script that references market data, your impact metrics, and the equity component.

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Quick “starter” draft (you can edit or ask me to expand)

1️⃣ One‑page résumé outline

[Your Name]
[Phone] • [Email] • [LinkedIn] • [GitHub/Portfolio]

PROFESSIONAL SUMMARY
Seasoned compiler engineer with 7+ years building production‑grade back‑ends (LLVM, proprietary GPU pipelines) and 4 years leading distributed, high‑performance teams. Proven track record of delivering JIT and AOT compiler features that cut compile latency by up to 35 % and enabled new AI workloads on NVIDIA GPUs. Passionate about bridging hardware capabilities with software abstractions to accelerate AI, graphics, and scientific computing.

EXPERIENCE
Senior Compiler Engineer / Technical Lead – [Current/Most Recent Company] – [City, Country] – [MM/YYYY–Present]
- Lead a 9‑engineer, globally‑distributed team delivering the LLVM‑based GPU backend for a next‑gen AI accelerator; shipped 3 major releases on schedule.
- Designed and implemented a custom JIT pipeline that reduced kernel launch overhead from 12 ms to 7 ms, directly improving end‑to‑end training throughput by 22 %.
- Partnered with graphics, CUDA, and driver teams to align ABI and code‑gen conventions across 4 product lines, ensuring binary compatibility and a unified developer experience.
- Instituted performance‑analysis tooling (perf‑metrics, custom LLVM passes) that identified and eliminated 15 % of redundant memory copies in generated code.
- Mentored 5 junior engineers; introduced a peer‑review process that lifted code‑quality scores (SonarQube) from “C” to “A‑”.

Compiler Engineer – [Previous Company] – [City, Country] – [MM/YYYY–MM/YYYY]
- Developed LLVM back‑end extensions for a heterogeneous compute platform, adding support for vector‑wide instructions and custom memory hierarchies.
- Contributed to open‑source MLIR dialects for tensor operations, later adopted by the company’s deep‑learning compiler stack.
- Automated regression testing for code‑gen correctness across 200+ GPU kernels, cutting nightly test time by 40 %.

[Add any additional relevant roles, internships, or research]

EDUCATION
M.S. Computer Science – [University] – [Year]
B.S. Computer Engineering – [University] – [Year]

TECHNICAL SKILLS
- Languages: C++ (14/17/20), Python, Rust (basic)
- Compilers: LLVM, Clang, MLIR, GCC, proprietary GPU back‑ends
- Tools: CMake, Bazel, Git, Gerrit, Perf, Nsight Compute, Valgrind
- Parallelism: CUDA, OpenCL, OpenMP, SYCL, GPU‑wide SIMD
- Performance analysis: LLVM‑Pass instrumentation, roofline modeling, profiling suites
- Leadership: Agile/Scrum, OKR planning, cross‑functional stakeholder management

2️⃣ Sample cover‑letter paragraph (first two)

Dear Hiring Committee,

I am excited to apply for the Backend Compiler Manager role (JR2011455) on NVIDIA’s GPU Software organization. With over seven years of hands‑on experience building production‑grade compilers—including LLVM‑based back‑ends and proprietary JIT pipelines for GPU accelerators—and four years of technical leadership of globally distributed teams, I have a proven ability to turn ambitious hardware capabilities into reliable, high‑performance software that fuels AI, graphics, and scientific workloads. NVIDIA’s vision of being “the AI computing company” aligns perfectly with my passion for pushing the limits of parallel programming and machine‑learning compilers.

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Next steps

1. Send me your current résumé (or a bullet list of your roles/achievements) and any specific metrics you have (e.g., compile‑time reductions, team size, release cadence).
2. Tell me the tone you prefer for the cover letter (formal, enthusiastic, concise).
3. Let me know if you want interview prep—I can generate mock questions and model answers for both the deep‑technical and leadership portions.

Just reply with the information you have, and I’ll craft the polished documents (or prep plan) for you right away! 🚀