DL Performance Software Engineer - LLM Inference

NVIDIA Corporation; Toronto; On-site; CAD 135,000 - 220,000; Full time

Benefits offered by this job

Equity

Benefits

Hybrid work

Job summary

NVIDIA Corporation seeks highly skilled software engineers to build AI inference systems, optimize GPU kernels, and push the frontier of accelerated computing for AI. You’ll work across inference performance, kernels, training, serving, and research teams on open‑source projects like vLLM.

Requirements include a CS/CE/SE degree, 5+ years’ experience, and strong Python plus C/C++, Go, or Rust skills; CUDA and Nsight proficiency is valued. Hybrid work and equity benefits are offered.

Qualifications

• Bachelor’s, Master’s or PhD in CS/CE/SE.
• 5+ years of industry software experience or equivalent research experience.
• Strong programming in Python and one of C/C++, Go, or Rust.

Responsibilities

• Contribute features to vLLM and NVIDIA GPU-backed models.
• Profile and optimize the inference framework and kernels.
• Architect novel frameworks and runtime optimizations for inference infrastructure.
• Publish original research advancing ML systems performance.
• Develop, optimize and benchmark GPU kernels with fusion and memory layout optimizations.

Skills

Python

C/C++

Go

Rust

CUDA

Nsight

Education

Bachelor's degree in CS/CE/SE

Master's degree in CS/CE/SE

PhD in CS/CE/SE

Tools

vLLM

SGLang

PyTorch

Triton

MLIR/LLVM

XLA

CUTLASS

Job description

We are seeking highly skilled and motivated software engineers to join us and build AI inference systems that serve large-scale models with extreme efficiency. You’ll architect and implement high-performance inference software, optimize GPU kernels, drive industry benchmarks, and work with state-of-the‑art research techniques to improve serving efficiency. You’ll collaborate across inference performance, kernels, training, large-scale serving, and research teams to push the frontier of accelerated computing for AI.

What you’ll be doing:

• Contribute features to vLLM that empower the newest models with the latest NVIDIA GPU hardware features and serving runtime algorithms.
• Profile and optimize the inference framework (vLLM) with methods like speculative decoding, 5D Parallelism, and prefill‑decode disaggregation.
• Architect novel frameworks and runtime optimizations for inference infrastructure, benchmarking, and kernels.
• Conduct and publish original research that advances the Pareto frontier in ML Systems; survey recent publications and find a way to integrate research ideas and prototypes into production‑grade, open‑source software.
• Develop, optimize, and benchmark GPU kernels (both hand‑tuned and compiler‑generated) using techniques such as fusion, autotuning, and memory/layout optimization.

What we need to see:

• Bachelor’s, Master’s, or PhD degree in Computer Science (CS), Computer Engineering (CE) or Software Engineering (SE).
• 5+ years of industry experience in software engineering or equivalent research experience.
• Strong programming skills in Python and one of C/C++, Go, or Rust.
• Solid CS fundamentals: algorithms & data structures, operating systems, computer architecture, parallel programming, software engineering, distributed systems, deep learning theories.
• Knowledgeable and passionate about performance engineering in ML frameworks (e.g., PyTorch) and inference engines (e.g., vLLM and SGLang).
• Familiarity with GPU programming and performance: CUDA, memory hierarchy, streams, NCCL; proficiency with profiling/debug tools (e.g., Nsight Systems/Compute).
• Excellent debugging, problem‑solving, and communication skills; ability to excel in a fast‑paced, multi‑functional setting.

Ways to Stand out from the Crowd

• Experience developing major features and optimizations for LLM inference engines (e.g., vLLM, SGLang).
• Hands‑on work with LLM inference and training runtimes (deploying LLMs to production, large‑scale LLM pre‑training and RL), ML compilers and DSLs (e.g., Triton, CuTe, MLIR/LLVM, XLA), GPU libraries (e.g., CUTLASS) and features (e.g., CUDA Graph, Tensor Cores).
• Experience with speculative decoding training and runtime features: tree‑structured drafting, parallel drafting, diffusion LLMs, DFlash, EAGLE.
• Contributions to open‑source projects and/or publications; please include links to GitHub pull requests, published papers and artifacts.

At NVIDIA, we believe artificial intelligence (AI) will fundamentally transform how people live and work. Our mission is to advance AI research and development to create groundbreaking technologies that enable anyone to harness the power of AI and benefit from its potential. Our team consists of experts in AI, systems and performance optimization. Our leadership includes world‑renowned experts in AI systems who have received multiple academic and industry research awards.

#LI‑Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 135,000 CAD - 185,000 CAD for Level 3, and 170,000 CAD - 220,000 CAD for Level 4.

• You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 10, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.