Senior MLIR AI Compiler Engineer for GPU Performance

NVIDIA AI; Santa Clara (CA); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking an engineering professional in Santa Clara, CA to develop MLIR-based graph representations and optimizations for future GPU architectures. You will collaborate with framework and hardware teams to enable new model patterns and GPU features, and define APIs and MLIR dialects while performing performance optimizations.

The role requires strong C/C++ and Python skills, independent work, and leadership in developer efforts within a fast-moving team focused on AI and GPU computing.

Qualifications

• 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.
• Experience with compiler technologies such as MLIR, XLA, and LLVM.
• Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and testing.

Responsibilities

• Develop MLIR-based graph representations and optimizations for future GPU architectures.
• Partner with framework and hardware teams to enable new model patterns and upcoming GPU architectural features.
• Define APIs and MLIR dialects, conduct performance optimizations and analysis, implement compiler optimizations and kernel generation for neural networks, and contribute to other general software engineering work.

Skills

MLIR

C/C++

Python

Performance analysis

Debugging

Leadership

Education

Bachelor's/Master's/Ph.D. in CS/CE or related

Tools

MLIR

XLA

LLVM

Job description

NVIDIA is seeking an engineering professional in Santa Clara, CA to develop MLIR-based graph representations and optimizations for future GPU architectures. You will collaborate with framework and hardware teams to enable new model patterns and GPU features, and define APIs and MLIR dialects while performing performance optimizations.

The role requires strong C/C++ and Python skills, independent work, and leadership in developer efforts within a fast-moving team focused on AI and GPU computing.