Sr Staff ML Forward Deployed Engineer, Enterprise GenAI

Scale AI · London, UK · Enterprise Engineering · listed July 7, 2026

The shape of it

Seniority
Staff
Experience asked
7+ years
Where
Not stated
Requirements listed
3
Length
538 words

In the posting’s own words

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our product in a fast-paced environment. The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will be responsible for owning large new areas within our product, working across backend, frontend, and interacting with LLMs and ML models. You will solve hard engineering problems in scalability and reliability.

What it asks for · 3

  • Proficient in Python or Javascript/Typescript, and SQL
  • Experience with Kubernetes
  • Experience with major cloud providers (AWS, Azure, GCP)

Tools and skills named

Models & research
  • LLM3×
  • Machine learning2×
  • Inference
Cloud & infra
  • AWS
  • Azure
  • Distributed systems
  • GCP
  • Kubernetes
Languages
  • JavaScript
  • Python
  • SQL
  • TypeScript

Words the posting leans on

  • experience6×
  • product5×
  • engineering3×
  • llms3×
  • areas2×
  • backend frontend2×
  • evaluation2×
  • generative platform2×
  • interacting2×
  • large2×
  • models2×
  • technologies2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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How this page was made

An automated read of a public job posting, fetched August 25, 2026 and last changed by Scale AI on August 4, 2026. Every list above is pulled from the posting’s own sentences — nothing rewritten, nothing added, no judgment about the role or the company. Counts and seniority are read off the text by rule, so they can be wrong where the posting is unusual. The original is the only thing that binds. Openings close without warning; check the source before spending an evening on it.