Member of Technical Staff - Compilers

About the Company

Gimlet is building the next generation of AI infrastructure: large-scale AI datacenters and the orchestration platform that coordinates them. We work with foundation labs, hyperscalers, and AI-native companies to power production workloads at massive scale.

Responsibilities

• Build compiler and runtime infrastructure that improves latency, throughput, and efficiency for large-scale AI inference workloads
• Design execution strategies that intelligently partition and coordinate workloads across heterogeneous hardware
• Develop compiler optimizations spanning IR transformations, scheduling, memory movement, and kernel orchestration
• Enable new model architectures and serving techniques to run efficiently in production environments
• Influence the architecture of an execution platform that will help define how AI workloads are deployed

Requirements

• Strong systems and performance engineering fundamentals
• Experience building compiler systems, compiler-adjacent infrastructure, or execution/runtime systems
• Experience implementing IR transformations, compiler passes, lowering logic, or code generation systems
• Ability to reason about execution behavior, memory systems, scheduling, and hardware efficiency
• Strong software engineering skills in C++ and/or Python

Preferred Qualifications

• Experience with MLIR, LLVM, XLA, TVM, Triton, or similar compiler/runtime infrastructure
• Experience optimizing ML inference or serving workloads
• Familiarity with runtime systems, kernel dispatch, launch APIs, or memory allocators
• Experience working with GPUs, AI accelerators, or heterogeneous hardware systems
• Experience profiling and debugging performance-critical systems
• Familiarity with scheduling, partitioning, or kernel-level optimizations