Software Engineer, ML Infrastructure

What you'll do

• Design and build agentic systems to accelerate the ML development lifecycle across DoorDash, Wolt, and Deliveroo.
• Implement infrastructure that allows AI agents to propose, run, and evaluate modeling experiments.
• Build agentic developer support tools for training jobs, debugging pipelines, and reviewing model deployments.
• Develop evaluation and observability frameworks to measure agent behavior and catch regressions early.
• Establish production standards including reliability, safety guardrails, cost controls, and monitoring for agentic workflows.
• Translate manual ML workflows into durable, reusable platform capabilities by partnering with data science and platform teams.
• Own well-scoped components end-to-end from initial design through production deployment.

What we're looking for

• B.S., M.S., or PhD in Computer Science or equivalent.
• 2+ years of industry experience in software engineering.
• Hands-on experience building ML infrastructure in production, including data pipelines, training platforms, and model serving.
• Strong backend engineering fundamentals, especially in Python and distributed systems.
• Experience operating systems in production, including testing, observability, debugging, and reliability.
• Proficiency in using AI coding tools across the software development lifecycle.
• Experience building LLM-powered applications or AI agents, including tool use and orchestration (preferred).
• Experience with ML platforms, Kubernetes, or cloud infrastructure (AWS/GCP) (preferred).