Senior Compiler Engineer, AI Inference Performance

Nvidia

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA · Austin, TX
Salary: $152,000–$241,500 / yr
Posted: 100 days ago
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $205k

This role $197k

$141k most similar roles pay here $252k

This role pays less than 54% of similar roles. Most pay $174,375–$235,750 — the shaded band above. At the midpoint, this role pays about $197k versus about $205k for comparable roles.

Based on 240 similar postings.

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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 855 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 843 roles with salary data.

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At a glance

TL;DR · Senior Compiler Engineer, AI Inference Performance

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NVIDIA seeks an AI & Deep Learning Compiler Engineer to join its DLC team, focusing on advancing the inference engine for large-scale applications in areas like generative AI and image classification. This role involves collaborating with deep learning software framework teams and GPU architecture experts to enhance public APIs, optimize performance, and develop compiler techniques tailored for future NVIDIA GPUs. Ideal candidates hold a degree in computer science or related field and possess experience with compiler technologies such as MLIR and LLVM, along with proficiency in CPU and GPU architectures. Strong understanding of deep learning models and frameworks like PyTorch is essential, alongside skills in GPU kernel authoring and performance analysis using tools like Nsight Compute.

Skills

MLIR LLVM XLA Triton PyTorch JAX Nsight Compute CUDA C++ Python CI/CD

What you'll do

Define public APIs for deep learning software frameworks.
Optimize performance and analyze AI workloads using compiler techniques.
Implement ahead-of-time and just-in-time compilation methods.
Craft compiler technologies to enhance inference engine performance.
Author GPU kernels and perform analysis with tools like Nsight Compute.

What we're looking for

Bachelor’s, Master’s or Ph.D. in relevant field.
Experience with compiler technologies like MLIR, LLVM, XLA.
Proficiency in CPU and GPU architecture.
Deep understanding of deep learning models and frameworks.
Ability to author GPU kernels and analyze performance.
Mentoring experience for early-career engineers is beneficial.
Track record in new hardware bring-up is preferred.