Deep Learning Compiler Verification Engineer

Details

NVIDIA is building the next generation of compiler technologies to accelerate deep learning workloads. The role focuses on implementing compiler verification software and related infrastructure for AI systems, working alongside GPU computing, compiler, architecture, and systems software teams.

Responsibilities

• Develop and maintain systems that reason about correctness in deep learning compilers across graph transformations, IR lowering, and GPU execution.
• Work with deep learning compiler and architecture teams to analyze and validate optimizations, including graph rewrites in MLIR, fusion passes, and mixed-precision transformations, ensuring they preserve semantics and numerical behavior.
• Implement and extend test generation systems that use deep learning solutions and analysis methods for in-depth testing.
• Explore the combinatorial space of model topologies, precision modes, and hardware targets.
• Improve methods for measuring functional quality and performance as models, compiler stacks, and hardware evolve.

Requirements

• Bachelor's, master's, or doctoral degree in Computer Science, Computer Engineering, Mathematics, or equivalent experience.
• At least 2 years of hands-on software engineering experience, including experience in compiler development, deep learning systems, or compiler verification.
• Proficiency in Python or C++.
• Experience with a major deep learning framework such as PyTorch, JAX/XLA, TensorRT, or a similar framework, including model execution, graph representation, or runtime behavior.
• Strong problem-solving and debugging skills, including the ability to reason about model behavior and compiler-generated code, investigate correctness issues, and collaborate with teammates to resolve edge-case failures.

Preferred Qualifications

• Experience with compiler technologies such as LLVM, MLIR, TVM, or XLA, and familiarity with compiler passes, IR semantics, or correctness testing.
• Exposure to formal methods or language specification, including type systems, program semantics, or proof-based verification.
• Experience with deep learning model internals such as quantization, operator fusion, mixed precision, or graph-level optimization.

Compensation and Benefits

The expected base salary range is USD 116,000–189,750 per year. Compensation is determined based on location, experience, and other objective job-related factors. The role also includes eligibility for equity and benefits.

NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer. Applications will be accepted at least until November 4, 2026.