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AI Engineer

Job in City Of London, Central London, Greater London, England, UK
Listing for: iO Associates
Contract position
Listed on 2026-07-11
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, DevOps
Salary/Wage Range or Industry Benchmark: 110700 - 166050 GBP Yearly GBP 110700.00 166050.00 YEAR
Job Description & How to Apply Below
Location: City Of London

AI Engineer – Defence Consultancy (6-Month Contract)

A defence consultancy is seeking an experienced AI Engineer to design, develop, and deploy machine learning solutions for secure, mission-critical environments. You will work across the full development lifecycle, from initial design to model deployment, optimization, and production support.

  • Position Type: 6-Month Contract
  • Security Requirement: Must hold an active SC-DV Clearance
Key Responsibilities
  • Development: Design and build AI-enabled applications using Python, machine learning frameworks, and Generative AI/LLM components.
  • Pipelines: Develop and optimize Retrieval-Augmented Generation (RAG) pipelines, vector databases, and scalable data processing streams.
  • MLOps: Implement model deployment, monitoring, testing, and lifecycle management using standard CI/CD and containerized workflows.
  • Architecture: Contribute to technical design decisions, trade-off analyses, and technology stack selection.
  • Collaboration: Work alongside cross-functional teams to translate complex requirements into secure, scalable, production-ready AI systems.
Requirements
  • Vetting: Active SC Clearance and British Citizenship are mandatory for this consultancy role.
  • Core Tech: Solid professional experience with Python and frameworks like PyTorch, Tensor Flow, or Scikit-Learn.
  • GenAI: Hands-on experience developing LLM-based applications, RAG pipelines, and prompt engineering.
  • Infrastructure: Experience deploying applications in cloud environments (AWS, Azure, or GCP) using Docker and Kubernetes.
  • Engineering: Strong software engineering fundamentals, including version control, testing, and API/microservices architecture.
  • Experience with MLOps platforms (e.g., MLflow, Sage Maker) or agentic AI frameworks.
  • Familiarity with secure development practices or regulated/high-compliance environments.
  • Background in NLP, computer vision, or data engineering platforms.
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