Software Engineer, Machine Learning Infrastructure

Software Engineer, Machine Learning Infrastructure - Generative AI
About the Team

Deliveroo's GenAI Platform team sits within Machine Learning Platform and builds the shared infrastructure that helps Door Dash, 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. A central pillar of that work is running frontier open-weight LLMs and VLMs (such as GLM, Qwen, Kimi, and Deep Seek) ourselves - real-time GPU serving, high-throughput batch inference, and fine-tuning on autoscaling GPUs - delivering large cost and latency wins (for example, a billion embeddings produced roughly 20× cheaper and visual models served roughly 72% cheaper).

We also own core platform surfaces including the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution.

You will join a small, high-leverage team building production infrastructure for Generative AI at Deliveroo and Door Dash, with a primary focus on our open-weights model platform spanning inference and fine-tuning: real-time GPU serving, high-throughput batch inference, and model fine-tuning. You’ll work across model serving and inference engines, fine-tuning and training pipelines, GPU autoscaling and utilization, batch pipelines, backend services, and observability.

This role is ideal for an engineer who enjoys pushing the cost/performance frontier of GPU inference and fine-tuning in a fast-moving technical area where product needs, model capabilities, vendor ecosystems, and cost/performance tradeoffs are evolving quickly.

• Build the infrastructure that helps Deliveroo teams move GenAI ideas from prototype to production, increasing the velocity of business impact from AI across the company.
• Work on our open-weights serving stack - real-time GPU endpoints, high-throughput batch inference, and fine-tuning (SFT/DPO/LoRA) - alongside the LLM Gateway, Agent Gateway, evals infrastructure, guardrails, and cost attribution.
• Design scalable, high-performance systems for model serving, batch inference, GPU autoscaling, and fine-tuning that power real customer and internal automation use cases
• Push the cost and latency frontier of GPU inference - turning batch jobs that took days into hours and cutting inference cost by multiples - while giving product teams a clean choice across open-weight and closed-source 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 Door Dash, Wolt, and Deliveroo to turn emerging GenAI capabilities into durable platform primitives.
• Shape the future of the centralized GenAI platform - including emerging directions such as reinforcement learning (RLHF/RLVR), agent optimization, and other post-training and agentic techniques - enabling the next generation of AI-powered products, agents, automation, and personalization.

• BSc, MSc, or PhD in Computer Science or equivalent
• 3+ 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.
• Hands‑on experience with LLM inference and/or fine‑tuning of open‑weight models in production - serving (latency, throughput, batching, autoscaling, GPU utilization) and/or fine‑tuning (SFT/DPO/LoRA).
• Ability to work across ambiguous, fast‑moving technical areas and turn customer use cases into reusable platform capabilities
• Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating…