Overview We are seeking a highly skilled Compiler Engineer with experience in MLIR (Multi-Level Intermediate Representation) and performance-critical code generation. The ideal candidate will focus on designing and implementing compiler infrastructure to generate high-performance kernels for AI, and machine learning. This role bridges advanced compiler technology with systems optimization, enabling domain-specific performance across heterogeneous architectures (GPUs and accelerators). Responsibilities: Compiler Development and Optimization Design and implement MLIR-based compiler passes for lowering, optimization, and code generation Build domain-specific dialects to represent compute kernels at multiple abstraction levels Develop performance-tuned transformation pipelines targeting vectorization, parallelization, and memory locality High-Performance Kernel Generation Generate and optimize kernels for linear algebra, convolution, and other math-intensive primitives Ensure cross-target portability while achieving near hand-tuned performance Collaborate with hardware teams to integrate backend-specific optimizations Performance Engineering Profile generated code and identify performance bottlenecks across architectures Implement optimizations for cache utilization, prefetching, and scheduling Contribute to auto-tuning strategies for workload-specific performance Collaboration and Research Work closely with ML researchers, system architects, and runtime engineers to co-design kernel generation strategies Stay up to date with developments in MLIR, LLVM, and compiler technologies Publish or contribute to open-source MLIR/LLVM communities where appropriate Qualifications: Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.