Member of Technical Staff - Compilers
About Us
Gimlet is building the next generation of AI infrastructure: large-scale AI datacenters and the orchestration platform that coordinates them.
The future of AI will require vastly more compute than exists today. But as AI workloads become more complex and new hardware architectures emerge, simply deploying more GPUs isn't enough. The challenge is making increasingly diverse compute work together.
Gimlet's platform intelligently partitions and routes workloads across heterogeneous hardware, enabling step-function improvements in performance and efficiency. Customers deploy through production-grade APIs without needing to think about hardware selection, placement, or optimization.
We work with foundation labs, hyperscalers, and AI-native companies to power production workloads at massive scale and help define the infrastructure layer for the future of AI.
ABOUT THE ROLE
Gimlet Labs is seeking a Member of Technical Staff focused on compiler infrastructure for ML execution systems, spanning IR transformations, runtime systems, kernel orchestration, scheduling, and serving optimization.
You will help build the execution stack that transforms modern AI workloads into efficient programs running across heterogeneous hardware. The work spans runtime systems, compiler infrastructure, scheduling, memory movement, kernel orchestration, and serving optimization for large-scale inference workloads.
This is not a traditional language compiler or backend code generation role. We are looking for engineers who think deeply about execution behavior: IR transformations, runtime optimization, scheduling, memory locality, kernel composition, distributed execution, and heterogeneous serving infrastructure.
WHAT YOU WILL WORK ON
- Design and implement compiler and runtime pipelines for large-scale AI inference workloads
- Build and evolve IR transformations, lowering passes, and execution optimizations...