Research and Pathfinding Internship: AI Workload Compiler Optimization for CPU and GPU

Job description

Job Details: Job Description: Join an Intel's Datacenter and AI Software Pathfinding team to advance compiler infrastructure for heterogeneous AI workloads. This internship focuses on developing novel optimization techniques for AI kernel compilation targeting both CPU (Intel AMX/AVX-512) and GPU architectures from a unified representation interfacing with MLIR/LLVM framework. Project Context: Modern AI systems are increasingly heterogeneous: CPUs handle small models, tool execution, feature engineering, and orchestration logic, while GPUs focus on large matrix operations and attention mechanisms of larger models. However, existing compiler frameworks struggle to generate optimized code for both architectures from the same high-level representation (e.g. Helion/Triton DSL). This internship addresses this challenge by integrating hierarchical optimization abstractions with equality saturation techniques into an MLIR-based compilation pipeline. The goal is to enable automatic discovery and autotuning of high-performance fused kernels through exhaustive algebraic exploration combined with target-specific scheduling decisions. What You'll Work On: You will explore the design and implem...