Ollama
Ollama is the easiest way to automate your work using open models, while keeping your data safe.
- Open roles
- 8
- New role every
- ~11.2 days
Company signals
Score: 88Job facts
- Location
- Palo Alto, California, United States of America
- Workplace
- Onsite
- Type
- Full-time
- Department
- Engineering
- Posted
- Jul 09, 2026
Last verified live 4 days, 7 hours ago · checked directly on the company's Ashby
Software Engineer, Cloud
at Ollama
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
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Build and scale the inference platform that serves every request from ollama.com.
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Design the routing and capacity layer that places workloads across GPUs and regions for cost, latency, and availability.
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Own multi-tenant infrastructure: isolation, quotas, usage metering, billing, and Pro/Max/team/enterprise tiering.
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Build the reliability, observability, and cost controls for our team and customers
You may be a fit if
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You have deep experience with high-throughput, low-latency distributed systems — inference serving, traffic routing, real-time data pipelines, or large-scale APIs.
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You're comfortable with cost/performance tradeoffs at scale and have owned a production service end-to-end.
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You've worked with Kubernetes, GPU scheduling, or inference infrastructure.
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You think in terms of reliability, SLOs, and honest capacity planning.
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Bonus: experience building an inference platform, GPU fleet management, or billing/metering for an AI service.