Scale AI Applied AI
AI Infrastructure Engineer, Serving Platform
- Location London, UK
- Seniority senior
- Posted 2026-07-24
Original posting ↗ You apply on the company site — we never collect applications.
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role details
Build and maintain high-performance systems for serving large language models (LLMs) at scale.
Summary generated by AI from the original posting.
Hard requirements to check first
- Clearance：not mentioned in the posting
- Work auth：not mentioned in the posting
Skills
PythonGoRustKubernetesDockerTerraformAWSGCPObservabilityC++
Excerpt from the original posting
As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments. The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company. You will: - Build and maintain fault-tolerant, high-performance systems for serving LLMs and other models at scale. - Build an internal platform to empower LLM capability discovery. - Collaborate with researchers and engineers to integrate and optimize models for production and research use cases. - Conduct architecture and design reviews to uphold best practices in system design and scalability. - Develop monitoring and observability solutions to ensure system health and performance. - Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment. Ideally you'd have: - 4+ years of experience building large-scale, high-performance backend systems. - Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++). - Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.) - Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc. - Experience with containers and orchestration tools (e.g., Docker, Kubernetes). - Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform). - Proven ability to solve complex problems and work independently in fast-moving environments. Nice to haves: - Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications t…