Applied AI Engineer, Global Public Sector: End-to-End AI

scaleai

Greater London

On-site

GBP 90,000 - 120,000

Full time

14 days+

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Job summary

Scale’s rapidly growing Global Public Sector team is hiring Applied AI Engineers to build custom end-to-end AI applications for our public sector clients using the latest developments in the field of AI.

You will also get the opportunity to develop and be part of creating custom datasets, evaluations, and fine-tuning these sophisticated models to maximize performance and apply on real world use cases with global reach.

Qualifications

  • Bachelor's degree in Computer Science, Mathematics or related field
  • 7+ years of post-graduation engineering experience
  • 2+ years applying AI/ML in production
  • Familiarity with cloud-based machine learning tools and platforms (AWS, GCP, Azure)

Responsibilities

  • Partner with public sector clients to define AI-driven solutions
  • Build and deploy end-to-end AI applications into production leveraging latest developments from the biggest AI labs, and open source models
  • Collaborate with cross-functional teams, including data annotation specialists, to create high-quality training datasets
  • Design and maintain robust evaluation frameworks to ensure the reliability and effectiveness of AI models
  • Participate in customer engagements, including occasional travel (approximately two weeks per quarter)
  • Contribute to the scaling of AI capabilities in the public sector through hands-on knowledge sharing

Skills

Python
TypeScript/JavaScript
Java
C++
AI/ML deployment
Cloud platforms
Communication skills
Startup experience

Education

Bachelor's degree in Computer Science or Mathematics or related field

Job description

Scale’s rapidly growing Global Public Sector team is hiring Applied AI Engineers to build custom end-to-end AI applications for our public sector clients using the latest developments in the field of AI.

You will also get the opportunity to develop and be part of creating custom datasets, evaluations, and fine-tuning these sophisticated models to maximize performance and apply on real world use cases with global reach.

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