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Salary
≈ $148k – $311k per year (Estimated)
Location
In office (Palo Alto)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Jul 9, 2026. Ollama scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Ollama is a software company that makes it easy to run open models and automate work with them while keeping data safe. It began as an open-source local-first runtime and has grown into a developer network of 8.9 million monthly active developers, backed by Y Combinator, Benchmark, 8VC and Theory Ventures. The company is headquartered in Palo Alto, California, United States.

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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