Backed by Menlo and Sapphire.
About the role
As a Member of Technical Staff, you will build the systems that schedule, route, and coordinate AI workloads across Gimlet’s infrastructure. Different stages of an inference pipeline may run on different hardware, scale independently, and exchange state across the system. Your work will determine how those workloads are placed, coordinated, routed, recovered, and operated in production.
What they're looking for
- Experience building or operating distributed systems in production
- Strong software-engineering and systems fundamentals
- The ability to reason about concurrency, consistency, failure modes, and system tradeoffs
- Experience with scheduling, resource management, RPC, or asynchronous messaging
- A bachelor’s degree in a relevant field or equivalent practical experience
More about this role
Gimlet is building the first multi-silicon neocloud designed for fast, efficient AI inference.
We combine large-scale compute infrastructure with an execution platform that partitions AI workloads and maps each stage to the hardware best suited to run it.
We work with foundation labs, hyperscalers, and AI-native companies, giving our team access to technical problems spanning frontier models, production infrastructure, and emerging hardware.
As a Member of Technical Staff, you will build the systems that schedule, route, and coordinate AI workloads across Gimlet’s infrastructure.
Different stages of an inference pipeline may run on different hardware, scale independently, and exchange state across the system. Your work will determine how those workloads are placed, coordinated, routed, recovered, and operated in production.
You will work across scheduling, orchestration, control planes, APIs, and fault tolerance. You will design systems that make distributed infrastructure easier to operate, enable workloads to run reliably across a heterogeneous fleet, and partner with compiler, ML systems, networking, and infrastructure engineers to connect the full execution stack.
Build...
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