Member of Technical Staff - Compiler Engineer

The role

You will build the AI Compiler Stack to determine how AI workloads are represented, optimized, and executed across different hardware architectures. This involves scaling compiler architecture, optimizing end-to-end performance, and supporting new models and serving techniques.

What you will do

• Scale the compiler architecture to a growing set of heterogeneous compute architectures
• Work on abstractions, dialects, and lowering paths for new targets
• Optimize end-to-end performance including operator fusion and target-specific optimizations
• Implement execution-planning decisions for partitioning computation across devices
• Evaluate and integrate agent-driven kernel generation
• Support new models and serving techniques in production

Required qualifications

• Experience building ML compilers and runtimes with sharp focus on performance optimizations
• Experience with MLIR, LLVM, or comparable compiler infrastructure
• Experience designing intermediate representations, writing compiler passes, or implementing lowering and code-generation pipelines
• Strong C++ and/or Python skills
• A strong understanding of SSA, memory systems, scheduling, and hardware efficiency
• Experience with operator fusion, tiling, layout transformations, or memory planning
• Experience using profilers to investigate performance across software and hardware boundaries
• Experience with IREE, XLA, TVM, Triton, or similar ML compilers and programming tools

Nice to have

• Experience optimizing ML inference or model-serving workloads
• Familiarity with kernel dispatch, launch APIs, memory allocators, or runtime interfaces
• Experience across GPU and non-GPU accelerator architectures
• Experience with automated kernel generation, autotuning, or search-based optimization
• Contributions to open-source compiler infrastructure

About the company

Gimlet is building the first multi-silicon neocloud designed for fast, efficient AI inference. They combine large-scale compute infrastructure with an execution platform that partitions AI workloads and maps them to hardware.