Compiler Optimization Engineer

About the Role

We're looking for a Graph Optimization Compiler Engineer to own the middle tier of our AI compiler stack — the layer where high-level model graphs are transformed, simplified, and made ready for efficient code generation. You'll design and implement the optimization passes that make the difference between a model that runs and a model that flies. This role sits between our compiler front end and code generation backend. You'll work on graph-level transformations — fusion, layout optimization, dead code elimination, constant folding, and more — with a direct line of sight to the performance outcomes your work produces.

What You'll Do

• Design, develop, and maintain the graph optimization layer of our heterogeneous AI compiler
• Implement and extend graph-level transformation passes including operator fusion, layout propagation, dead code elimination, constant folding, and algebraic simplification
• Define and evolve our intermediate representation (IR) to support new optimization opportunities as ML model architectures advance
• Analyze performance data to identify optimization gaps and drive measurable improvements in throughput and latency
• Collaborate with front end and code generation teams to ensure clean IR interfaces and well-structured optimization pipelines
• Propose and prototype new optimization strategies in response to advances in model design and hardware capabilities
• Contribute to testing and validation infrastructure to ensure optimization correctness across model types and hardware targets