Senior Deep Learning Compiler Engineer

Nvidia

Confirmed live today Trusted

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CAAustin, TXRedmond, WA
Salary: $152,000–$241,500 / yr
Employment: Full-time
Posted: 18 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $210k

This role $197k

$140k $268k

below market most similar roles pay here above market

This role pays less than 58% of similar roles. Most pay $177,737–$241,750 — the blue band above. At the midpoint, this role pays about $197k versus about $210k 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 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior Deep Learning Compiler Engineer

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The Senior Deep Learning Compiler Engineer joins the Deep Learning Compiler team to develop the backbone of the inference engine across data centers, personal devices, automotive, and robotics. The role involves analyzing deep learning networks to develop compiler optimization algorithms, defining public APIs, and crafting compiler infrastructure techniques for neural networks. You will collaborate with software framework and hardware architecture teams to accelerate next-generation software while ensuring leading inference performance, fast build times, and reduced memory footprints. Required skills include C/C++, Python, and experience in performance analysis and compiler optimizations. Preferred technical proficiencies include CPU and GPU architecture, CUDA, OpenCL, MLIR, XLA, TVM, and LLVM. The work focuses on optimizing deep learning models and algorithms for large language models, generative AI, and speech recognition.

Skills

C++ Python CUDA OpenCL MLIR XLA TVM LLVM PyTorch GPU Architecture Compiler Optimization Deep Learning cross compilation Performance Analysis Kernel Generation

What you'll do

Analyze deep learning networks to develop compiler optimization algorithms.
Define public APIs and performance optimizations for deep learning software.
Craft and implement compiler infrastructure techniques for neural networks.
Develop high-performance GPU kernel generation with fast build times.
Perform performance analysis and debugging using C++, Python, and CUDA.
Implement Ahead-of-Time and Just-in-Time compiler features for inference.
Optimize software for systems with constrained resources like small memory and embedded platforms.

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.
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).
Experience with MLIR, XLA, TVM, LLVM, deep learning models, and frameworks like PyTorch (preferred).

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