About the role
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.
Agency Policy: Gimlet Labs does not accept unsolicited resumes from recruitment agencies or search firms. Any unsolicited resumes submitted without a signed agreement will be considered the property of Gimlet Labs, and no fees will be paid.