Junior AI/ML Engineer: Computer Vision & DL (SC Cleared)

SR2 REC LTD; Greater London; On-site; GBP 35,000 - 55,000; Full time

Job summary

SR2 REC LTD is seeking a Junior AI/ML Engineer to join a specialist team delivering computer vision and deep learning solutions for a major defence technology programme. You will work with AI researchers and senior engineers to develop, test and deploy AI models in real-world environments.

This role offers exposure to production-scale systems, MLOps practices, and cutting-edge techniques such as CNNs and transformers. A foundation in Python and ML, plus eagerness to learn, are essential.

Qualifications

• Active SC clearance (client will sponsor DV)
• Practical experience developing ML solutions using Python
• Experience with PyTorch or TensorFlow
• Understanding of deep learning, neural networks and computer vision
• Familiarity with CNNs, image processing or object detection
• Strong software engineering fundamentals, including Git and testing
• Good problem-solving skills and willingness to learn from experienced engineers

Responsibilities

• Develop, test and optimise machine learning and computer vision models
• Support the development of deep learning solutions using Python and PyTorch
• Assist with model training, validation, evaluation and deployment
• Contribute to scalable ML pipelines and production-quality software
• Collaborate with senior engineers to integrate AI models into operational systems
• Support testing, debugging and continuous improvement of AI applications

Skills

Python

PyTorch

TensorFlow

Deep learning

Computer vision

Git

Testing

Problem-solving

Tools

Docker

CI/CD

Cloud ML environments

NVIDIA GPUs

MLOps

Job description

SR2 REC LTD is seeking a Junior AI/ML Engineer to join a specialist team delivering computer vision and deep learning solutions for a major defence technology programme. You will work with AI researchers and senior engineers to develop, test and deploy AI models in real-world environments.

This role offers exposure to production-scale systems, MLOps practices, and cutting-edge techniques such as CNNs and transformers. A foundation in Python and ML, plus eagerness to learn, are essential.