Why this role stands out
This role offers a unique opportunity to build and scale a cutting-edge cloud inference platform at a rapidly growing company with a significant impact on the open-model ecosystem. You'll thrive here if you are a seasoned Software Engineer with expertise in distributed systems and a passion for building robust, high-performance infrastructure that serves millions of developers. Join a talented, fast-moving team and contribute to the future of AI accessibility.
Quick overview
Job description
Ollama is the most popular way for developers to access open models. What started as an open-source, local-first runtime is now the largest developer network in the open-model ecosystem: 8.9 million monthly active developers and over 67,000+ community-built integrations. We're backed by Y Combinator, Benchmark, 8VC, and Theory Ventures.
Our team is small and talent dense. We're flat, low-ego, and fast-moving. We like people who are truth-seeking, passionate, design-driven, and who enjoy shipping code.
About the role
You'll build Ollama’s cloud, a scalable inference platform that lets developers run large, capable open models in their workflow. You'll work on high-throughput, low-latency distributed systems — inference serving, GPU fleet management, routing, metering, and the platform that Pro, Max, Team, and Enterprise customers rely on to process trillions of tokens.
What you'll do
Build and scale the inference platform that serves every request from ollama.com.
Design the routing and capacity layer that places workloads across GPUs and regions for cost, latency, and availability.
Own multi-tenant infrastructure: isolation, quotas, usage metering, billing, and Pro/Max/team/enterprise tiering.
Build the reliability, observability, and cost controls for our team and customers
You may be a fit if
You have deep experience with high-throughput, low-latency distributed systems — inference serving, traffic routing, real-time data pipelines, or large-scale APIs.
You're comfortable with cost/performance tradeoffs at scale and have owned a production service end-to-end.
You've worked with Kubernetes, GPU scheduling, or inference infrastructure.
You think in terms of reliability, SLOs, and honest capacity planning.
Bonus: experience building an inference platform, GPU fleet management, or billing/metering for an AI service.
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