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Software Engineer, Cloud

Ollama · ollama.com
Palo AltoOn-site
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Straight from the company’s own careers site.

The job in short

A full-time on-site Software Engineer role at Ollama in Palo Alto. Skills mentioned: Kubernetes.

Kubernetes

Details

Found
38 d ago · posted 2026-07-09
Location
Palo Alto

Full 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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