Member of Technical Staff - Distributed Systems

About us

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.

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.

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.

What success looks like

In the first 12-18 months, you will:

Build scheduling and orchestration systems for heterogeneous compute

Design systems that manage independently scalable stages of distributed inference pipelines

Improve the reliability and fault tolerance of production AI infrastructure

Develop control planes and APIs that simplify how workloads are deployed and managed

Improve resource management and scheduling as Gimlet expands across new accelerator types, nodes, and data centers

Help the platform scale across additional hardware, nodes, and data centers

You may be a good fit if you have

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

Strong candidates may also have

Experience with Kubernetes or Kubernetes-adjacent systems beyond basic usage

Experience designing service-oriented architectures using RPC or asynchronous messaging

Familiarity with scheduling, queues, or resource management systems

Experience building reliable APIs and operating systems under high load

Software development experience in languages commonly used for systems development (e.g., Go, C++, Python)

Why join now?

Gimlet is expanding from its core technology into a production neocloud spanning new hardware, customers, and data centers.

Solve hard problems.

Own meaningful work.

Build for production.

Help define what’s next.

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