Applied AI Engineer, Global Public Sector

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

Applied AI Engineer for Scale AI's Global Public Sector team, focusing on building custom end-to-end AI applications for public sector clients, generating training data for LLMs, and providing AI advisory services. The role involves deploying AI solutions, creating datasets, fine-tuning models, and establishing evaluation frameworks.

What you'd actually do

  1. Partner with public sector clients to deeply understand their challenges and define AI-driven solutions
  2. Build and deploy end-to-end AI applications into production leveraging latest developments from the biggest AI labs, and open source models
  3. Collaborate with cross-functional teams, including data annotation specialists, to create high-quality training datasets
  4. Design and maintain robust evaluation frameworks to ensure the reliability and effectiveness of AI models
  5. Contribute to the scaling of AI capabilities in the public sector through hands-on knowledge sharing

Skills

Required

  • Python
  • TypeScript/JavaScript
  • Java
  • C++
  • applying AI/ML in production environments
  • deploying deep learning solutions
  • building generative/agentic AI applications
  • setting up evaluations pipelines
  • cloud-based machine learning tools and platforms (e.g. AWS, GCP, Azure)
  • problem-solving skills
  • data-driven approach to iterating on machine learning models and datasets
  • written and verbal communication skills

Nice to have

  • Experience working at a startup
  • founding engineer
  • building and deploying large-scale AI solutions
  • Arabic

What the JD emphasized

  • 2+ years of experience applying AI/ML in production environments
  • deploying deep learning solutions
  • building generative/agentic AI applications
  • setting up evaluations pipelines

Other signals

  • building custom end-to-end AI applications
  • generating high-quality training data for national LLMs
  • upskilling and advisory services to spread the impact of AI
  • deploying deep learning solutions
  • building generative/agentic AI applications
  • setting up evaluations pipelines