Senior Deep Learning Software Engineer, DLSim

The DL Performance Modeling Team's core mission is to deliver full stack simulation infrastructure for deep learning applications across a spectrum of GPUs.

We are now looking for a Deep Learning Software Engineer to help develop simulation infrastructure.

Responsibilities:

• Develop simulation backends that enable fast, scalable evaluation of AI workloads across NVIDIA compiler stacks.
• Improve deep learning compiler kernel code generation and computational graph optimization using analysis based on modeled scenarios and performance insight.
• Advance the modeling and optimization of datacenter-scale AI workloads and deployment scenarios.
• Partner with architects and software teams to evaluate future GPU features and guide silicon and system-level design decisions.

Requirements:

• A Masters (or equivalent experience) in Computer Science, Computer Engineering, or a related STEM field; PhD preferred.
• 3+ years of relevant experience in compiler optimization, architectural simulation, or related areas.
• Strong hands-on experience with MLIR and compiler infrastructure.
• Excellent C/C++ and Python programming skills, including software design, debugging, performance analysis, and test development.
• Strong communication and collaboration skills, with the ability to thrive in a fast-paced, multi-functional, outcome-focused environment.

Preferred Qualifications:

• Experience designing and building compiler frameworks or intermediate representations from the ground up.
• Deep understanding of LLM inference workloads and their implications for computer architecture.
• Hands-on experience implementing and optimizing complex AI workloads on CPUs, GPUs, or custom accelerators.

You will also be eligible for equity and benefits.