Software Engineer, Machine Learning Infrastructure - Gen AI

**About the Team** ------------------ DoorDash's GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps DoorDash, Wolt, and Deliveroo teams safely bring GenAI\-powered products, agents, automation, and personalization to production. Our mission is to increase the velocity of business impact from GenAI. We own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, open\-weights model serving and batch inference, guardrails, and cost attribution. **About the Role** ------------------ You will join a small, high\-leverage team building production infrastructure for Generative AI at DoorDash. You'll work across backend services, ML infrastructure, agent/tool orchestration, evaluation systems, model serving, batch inference, and observability. This role is ideal for an engineer who enjoys building reliable platform primitives in a fast\-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly. **You're excited about this opportunity because you will…** ----------------------------------------------------------- * Build the infrastructure that helps DoorDash teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company. * Work on production GenAI platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, open\-weights model serving, batch inference, fine\-tuning, guardrails, and cost attribution. * Design scalable systems for AI agents, MCP/tool orchestration, retrieval, batch inference, model serving, and evaluation workflows that power real customer and internal automation use cases * Help product teams choose the right model and vendor strategy across closed\-source and open\-weight models, with reliability, fallback, observability, and cost controls built in. * Build platforms that support rapid experimentation while