Software Engineer, Machine Learning Infrastructure - Generative AI
Core
Building production infrastructure for Generative AI evaluation, tracing, and observability to help DoorDash, Wolt, and Deliveroo teams safely bring GenAI products to production.
Role type
Machine Learning Infrastructure Engineer (Generative AI)
Builds
Unified evals platform, LLM observability systems, agent simulations, and backend services for model serving and guardrails.
Domain
Generative AI / Machine Learning Infrastructure / Observability
Deliverable
production ML models | infrastructure
Required skills
Python, distributed systems, backend engineering, production service/API development, data pipelines, observability, debugging, incident response, performance/cost optimization, LLM evaluation pipelines, tracing/scoring, offline/online quality metrics
Preferred skills
LLM-as-judge design, OpenTelemetry, agent simulation, streaming ingestion, vector databases, RAG, Kubernetes, cloud infrastructure (AWS/GCP)
Technologies
Python, OpenTelemetry, SQL, columnar/OLAP, Kubernetes, AWS, GCP
Responsibilities
Build evaluation SDKs and trace/score ingestion systems; design scalable systems for evaluation workflows and agent simulation; partner with ML engineers and data scientists to create platform primitives; raise quality bar for GenAI with trustworthy measurement tools; build platforms supporting rapid experimentation with production standards.
Seniority
Mid-level, hands-on IC