> Markdown version of [/jobs/ext/1458893-staff-software-engineer-foundation-model-inference](https://www.wearedevelopers.com/jobs/ext/1458893-staff-software-engineer-foundation-model-inference). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer- Foundation Model Inference - **Company:** Databricks - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $190,000.0 - $265,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Distributed Systems, Monitoring of Systems, Azure Machine Learning, Service-Oriented Architecture, Cloud Platform System, Pytorch, Delivery Pipeline, Large Language Models, Backend, Machine Learning Operations, Restful APIs, GPT, Automation Anywhere, Databricks - **Published:** July 27, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=23a7adb3924b5e5e ## About the Role We are looking for high-agency engineers who are excited to work on powering model inference at enterprise scale., * 8+ years of experience in backend or infrastructure engineering * Experience with distributed systems, scalable APIs, or cloud-native infrastructure * Experience with real-time serving, ML infrastructure, or GPU orchestration * Familiarity with service-oriented architecture, deployment pipelines, and system observability ## Description * Build LLM infrastructure powering large-scale inference workloads for customers through partner models (OpenAI, Anthropic, Gemini) and self-hosted models (Qwen, GPT-OSS, Llama) * Improve reliability, latency, and efficiency of distributed AI workloads * Collaborate with platform, infra, and ML teams to deliver seamless end-to-end experiences * Shape how developers and data scientists build and interact with AI on Databricks, * Exposure to platforms like SageMaker, Vertex AI, or Azure ML * Contributions to OSS projects like MLflow, PyTorch, Ray, vLLM, SGLang * Built developer platforms or internal tools supporting AI workflows Pay Range Transparency ## Related Videos - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Azure AI Foundry for Developers: Open Tools, Scalable Agents, Real Impact](https://www.wearedevelopers.com/videos/1541-azure-ai-foundry-for-developers-open-tools-scalable-agents-real-impact) - [Streaming AI Responses in Real-Time with SSE in Next.js & NestJS](https://www.wearedevelopers.com/videos/1630-streaming-ai-responses-in-real-time-with-sse-in-next-js-nestjs) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)