Software Engineer, Machine Learning Infrastructure - Gen AI
External
Doordash · San Francisco, CAPrepare for this interview
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About the role
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. 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 meeting production standards for latency, scale, monitoring, SLOs, playbooks, and operational excellence. Partner closely with ML engineers, product engineers, data scientists, and platform teams across DoorDash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives. Shape the future of DoorDash's centralized GenAI platform, enabling the next generation of AI-powered products, agents, automation, and personalization. We're excited about you because... B.S., M.S., or PhD. in Computer Science or equivalent 4+ years of industry experience in software engineering Strong backend engineering fundamentals, especially in Python and distributed systems. Experience building production services, APIs, data pipelines, or ML infrastructure at scale. Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization. Familiarity with machine learning workflows such as inference, evaluation, feature/data pipelines, model serving, or experimentation. Ability to work across ambiguous, fast-moving technical areas and turn customer use cases into reusable platform capabilities
Requirements
- Experience fine-tuning and serving open-weights LLMs in production
- Experience building and deploying AI agents in production
- Experience building and deploying MCP servers in production
- Experience with LLM gateways, model routing, vendor abstraction, or cost attribution
- Experience with eval systems, LLM observability, tracing, or LLM-as-judge workflows
- Experience with RAG, search, vector databases, or retrieval pipelines
- Experience with Kubernetes, cloud infrastructure (AWS/GCP), GPUs, or high-throughput batch systems
- Experience building developer platforms, internal platforms, or self-serve infrastructure
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