Applied AI Engineer, Enterprise

Scale AI Scale AI · Data AI · London, United Kingdom · Enterprise Engineering

Scale AI is seeking an Applied AI Engineer for their Enterprise team in London, UK. The role involves working with clients to build advanced AI agents and ML solutions using the Scale Generative Platform (SGP), focusing on enterprise needs such as cybersecurity and genomics. Responsibilities include owning AI strategy, leveraging SGP for agent development (including multimodal and tool-calling features), gathering business requirements, collaborating with clients and internal teams, and deploying production code. The ideal candidate has a strong engineering background, Python proficiency, and experience with cloud ML development. Familiarity with Generative AI in production is a plus.

What you'd actually do

  1. Own, plan, and optimize the AI behind our Enterprise customer’s deepest technical problems
  2. Leverage SGP to build the most advanced AI agents across the industry including multimodal functionality, tool-calling, and more
  3. Have experience gathering business requirements and translating them into technical solutions
  4. Meet regularly with customer teams onsite and virtually, collaborating cross-functionally with all teams responsible for their data and ML needs
  5. Push production code in multiple development environments, writing and debugging code directly in both our customer’s and Scale’s codebases

Skills

Required

  • Python
  • common libraries (ie numpy, pandas)
  • cloud technology stack (eg. AWS or GCP)
  • developing machine learning models in a cloud environment
  • gathering business requirements
  • translating them into technical solutions
  • writing and debugging code

Nice to have

  • software engineering best practices
  • Generative AI in real, production use cases
  • state of the art LLMs and their strengths/weaknesses

What the JD emphasized

  • build the most advanced AI agents
  • multimodal functionality
  • tool-calling
  • state of the art research and AI
  • state of the art LLMs

Other signals

  • building complex agents for enterprises
  • clients to build cutting edge products
  • clients to create ML solutions to satisfy their business needs
  • building next-generation AI cybersecurity firewalls
  • applying foundation genomic models