Senior Compiler Engineer, AI Inference Platforms

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CAAustin, TX
Salary: $152,000–$241,500 / yr
Employment: Full-time
Posted: 6 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $193k

This role $197k

$140k $252k

below market most similar roles pay here above market

This role pays more than 54% of similar roles. Most pay $151,000–$235,750 — the blue band above. At the midpoint, this role pays about $197k versus about $193k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1792 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1179 roles with salary data.

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At a glance

TL;DR · Senior Compiler Engineer, AI Inference Platforms

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The Senior Compiler Engineer, AI Inference Platforms joins the Deep Learning & AI Compiler team to develop the backbone of the inference engine for data centers, personal devices, automotive, and robotics. You will analyze deep learning networks to develop compiler optimization algorithms, define public APIs, and implement compiler techniques for AI workloads on future GPUs. The role involves collaborating with deep learning software framework and GPU architecture teams to accelerate software performance. Required skills include C/C++, Python, and experience with compiler technologies like MLIR, LLVM, XLA, and Triton. Candidates should possess expertise in performance analysis, debugging, and test design. The work focuses on delivering leading inference performance, fast build times, and reduced memory footprints for large language models, generative AI, and image classification.

Skills

C++ Python MLIR LLVM XLA Triton CUDA OpenCL PyTorch JAX GPU Architecture Nsight Compute Compiler Optimization Deep Learning Performance Analysis

What you'll do

Analyze deep learning networks to develop compiler optimization algorithms.
Define public APIs for the deep learning compiler.
Implement compiler techniques specifically for AI workloads and future NVIDIA GPUs.
Perform performance optimizations and analysis for deep learning software.
Develop software to accelerate the next generation of deep learning models.
Design and implement features for both Ahead-of-Time and Just-in-Time compilation.
Lead independent development efforts to define project goals and scope.

What we're looking for

Bachelor’s, Master’s, or Ph.D. in Computer Science, Computer Engineering, a related field, or equivalent experience.
3+ years of relevant work or research experience in performance analysis and compiler optimizations.
Experience with compiler technologies such as MLIR, LLVM, XLA, or Triton.
Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design.
Ability to work independently, define project goals and scope, and lead development efforts.
Strong interpersonal skills and the ability to work in a dynamic product-oriented team.
Proficiency in CPU and/or GPU architecture (preferred).
CUDA or OpenCL programming experience (preferred).
Understanding of deep learning models, algorithms, and frameworks such as PyTorch or JAX (preferred).
GPU kernel authoring and performance analysis using tools such as Nsight Compute (preferred).
Track record of success in mentoring early-career engineers and interns (preferred).
Track record on new hardware bring-up (preferred).

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