Senior DL Software Engineer, DLSim — Hardware & Simulation

Nvidia Corporation in; Santa Clara (CA); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Senior Deep Learning Software Engineer for the DLSim team to build fast, scalable simulation infrastructure for AI workloads on GPUs.

You will develop simulation backends, improve compiler kernel code generation, and collaborate with architects to evaluate future GPU features and guide system-level design decisions. A strong MLIR/Compiler background and C/C++/Python skills are essential.

Qualifications

• 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.

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.

Skills

MLIR

C/C++

Python

Compiler optimization

Architectural simulation

Education

Master's degree / PhD preferred

Tools

MLIR

Job description

NVIDIA is seeking a Senior Deep Learning Software Engineer for the DLSim team to build fast, scalable simulation infrastructure for AI workloads on GPUs.

You will develop simulation backends, improve compiler kernel code generation, and collaborate with architects to evaluate future GPU features and guide system-level design decisions. A strong MLIR/Compiler background and C/C++/Python skills are essential.