Deep Learning Compiler Verification Engineer

Responsibilities

• Develop and maintain components of systems to 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 (e.g., graph rewrites in MLIR, fusion passes, mixed-precision transformations), ensuring they preserve semantics and numerical behavior.
• Implement and extend test generation systems that use deep learning solutions and analysis methods to drive in-depth testing. These systems explore the vast combinatorial space of model topologies, precision modes, and hardware targets.
• Contribute to improving how we measure functional quality and performance as models, compiler stacks, and hardware continue to evolve.
• What we need to see
• BS, MS or PhD in Computer Science, Computer Engineering, Mathematics, or equivalent experience.
• 2+ years of hands-on software engineering experience, with experience in compiler development, deep learning systems, or compiler verification.
• Proficiency in Python or C++ and experience with one major DL framework. This could be PyTorch, JAX/XLA, TensorRT, or a similar framework. Experience should involve model execution, graph representation, or runtime behavior.
• Strong problem-solving and debugging skills — ability to reason about model behavior and compiler-generated code, investigate correctness issues, and collaborate with teammates to resolve edge-case failures.
• Ways to stand out from the crowd

Languages