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Technical Lead - AI​/ML & Computer Vision

Job in City Of London, Central London, Greater London, England, UK
Listing for: SR2
Full Time position Listed on 2026-11-12
Job specializations:
Salary/Wage Range or Industry Benchmark: 100000 - 140000 GBP Yearly GBP 100000.00 140000.00 YEAR

Job Description & How to Apply Below

Location: City Of London

Technical Lead - AI/ML & Computer Vision Defence Technology

We are seeking an experienced AI/ML Technical Lead to lead the engineering delivery of an advanced computer vision and machine learning platform for a high-profile UK defence technology programme.

Working with a specialist AI organisation, you'll play a key role in taking established, cutting-edge AI technology into full-scale operational deployment.

This is a hands-on technical leadership position, combining advanced machine learning engineering, architecture and delivery oversight.

Key Responsibilities

  • Provide technical leadership to a team of AI/ML and MLOps Engineers.
  • Lead the design, optimisation and deployment of advanced computer vision and deep learning systems.
  • Oversee scalable ML training, inference and deployment pipelines.
  • Guide technical architecture, engineering standards and best practices.
  • Work closely with stakeholders to integrate AI solutions into existing infrastructure.
  • Mentor engineers, resolve technical challenges and ensure successful delivery.

Essential Skills & Experience

  • Active SC clearance - client can sponsor DV
  • Extensive experience in Machine Learning, Deep Learning and Computer Vision
    .
  • Strong hands-on Python and PyTorch development skills.
  • Expertise in CNNs, Vision Transformers and neural network architectures.
  • Proven experience delivering production-grade AI/ML systems.
  • Previous technical leadership or principal engineering experience.
  • Strong understanding of MLOps, CI/CD, model deployment and scalable infrastructure.
  • Excellent stakeholder management and technical communication skills.

Desirable Experience

  • GPU optimisation, distributed training and inference acceleration.
  • Docker, Kubernetes, MLflow or Kubeflow.
  • Object detection, segmentation and large-scale imagery processing.
  • Edge AI and NVIDIA technologies.
  • Defence, aerospace or national security projects.
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