Machine Learning Engineer

SR2; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

SR2 is seeking a Senior Machine Learning Engineer to advance computer vision & deep learning capabilities in defence technology. You will design, implement, and optimise neural networks, taking research from concept to production deployment and continuous improvement in demanding operational environments.

The role focuses on building robust CV/ DL systems for edge devices, ensuring performance in resource-constrained platforms and real-time inference scenarios, with eligibility for BPSS/SC

Qualifications

• Strong Python development and mathematical foundations.
• Deep learning expertise using PyTorch or TensorFlow.
• Strong understanding of computer vision, model training and optimisation.
• Experience building production-grade ML systems.
• Exposure to MLOps, deployment pipelines or model retraining advantageous.
• Experience with real-time inference, GPU optimisation or edge AI desirable.

Skills

Python

Deep learning

Computer vision

Production ML systems

MLOps

Real-time inference

GPU optimisation

Tools

PyTorch

TensorFlow

Job description

Senior Machine Learning Engineer - Computer Vision & Deep Learning

Sector: Defence Technology / Advanced AI

The Company

We're partnering with a specialist AI company developing proprietary machine learning technology for defence, national security and mission-critical applications.

Unlike businesses integrating off-the-shelf AI models, this organisation develops its own neural network architectures, combining advanced deep learning with neuroscience-inspired approaches.

Its technology is deployed into real-world defence environments, supporting computer vision, perception and autonomous systems.

The Role

We're seeking a technically strong ML Engineer to develop, optimise and deploy advanced computer vision systems.

You’ll work across the full ML lifecycle, from designing novel neural networks and implementing research through to production deployment, model retraining and continuous improvement.

A key challenge is ensuring models perform reliably in demanding operational environments, including edge devices and resource-constrained platforms.

Requirements

• Strong Python development and mathematical foundations.
• Deep learning expertise using PyTorch or TensorFlow.
• Strong understanding of computer vision, model training and optimisation.
• Experience building production-grade ML systems.
• Exposure to MLOps, deployment pipelines or model retraining advantageous.
• Experience with real-time inference, GPU optimisation or edge AI desirable.

Why Join?

Develop proprietary AI technology from first principles and see your work deployed into operational defence systems.

Security: Eligibility for BPSS clearance and ideally SC clearance required