The Role

Supported by a newly secured public funding grant, we are initialising an intensive engineering phase to transition a proprietary, laboratory-validated technical imaging technology from a Technology Readiness Level (TRL) 4 Proof of Concept into an operationally ready, commercially viable TRL 7 multi-tenant AI SaaS platform. The platform leverages advanced machine learning models to automate high-precision feature detection, image normalisation, and automated data analysis for specialised business and research environments.

We are seeking a highly skilled Machine Learning Engineer specialising in Computer Vision to spearhead the development of our next-generation visual AI capabilities. In this role, you will bridge the gap between bleeding-edge AI research and production-grade software. You will be responsible for sourcing, fine-tuning, and turning "off-the-shelf" foundation models into highly optimised, tailored commercial features that extract deep value from visual datasets, specifically for automated AI colony detection and counting

What you'll bring to our team (key contributions)

• Take state-of-the-art, off-the-shelf computer vision foundation models and adapt, fine-tune, or compress them to suit our specific product use cases.

• Package and deploy machine learning models into production environments (ideally AWS cloud infrastructure), ensuring low latency, high throughput, and efficient GPU cost-optimisation.

• Architect scalable pipelines for data collection, automated data labelling, visual preprocessing, and dataset augmentation.

• Actively evaluate newly released open-source models, translating theoretical AI breakthroughs into practical, scalable features.

• Partner with backend, frontend, and product teams to expose model outputs smoothly via high-performance APIs.

Who you are (essential skills & attributes)

• 3+ years of commercial experience, specifically training, adapting, and deploying computer vision systems.

• Proven experience working with, fine-tuning, and customising large off-the-shelf vision models, including:

• • Meta SAM 3 (Segment Anything Model 3) or SAM 2 for advanced promptable object masking and real-time tracking. Modern architectures like YOLO26, YOLO11, or state-of-the-art Real-Time DEtection TRansformers (DETRs).

  • Self-supervised backbones such as DINOv2.

• Mastery of Python and deep learning ecosystems, specifically PyTorch or TensorFlow, alongside core toolkits like OpenCV.

• Strong experience deploying vision models at scale using AWS tools (e.g., Amazon EC2 GPU instances, Amazon SageMaker) alongside model optimisation frameworks like TensorRT or ONNX.

• Extensive experience working within fast-paced Agile delivery teams using frameworks such as Scrum/Kanban, and expert-level proficiency with project management tools, specifically Jira and Confluence.

Desirable / Nice-to-Have

• Experience implementing modern MLOps pipelines for automated model retraining, version control (e.g., DVC, MLflow), continuous deployment (CD for ML), and real-time model drift/performance monitoring.

• Prior commercial or academic experience applying computer vision to Life Sciences, Biotech, Medical Imaging, or Digital Pathology (e.g., cell segmentation, tissue analysis, fluorescent imaging, or lab automation datasets) is highly advantageous.

• Familiarity with Vision-Language Models (VLMs) or fine-tuning Multimodal Foundation Models for visual reasoning tasks.

• Proactive use of advanced, modern development workflows and agentic coding tools (e.g., Claude Code, Cursor, or GitHub Copilot) to accelerate development and testing loops.

Your journey so far (qualifications)

You will bring 3+ years of commercial experience to the role, specifically training, adapting, and deploying computer vision systems. Crucially, we firmly believe that the right person can come from any background, and your unique journey matters more than just a qualification.

Mandatory Grant Compliance & Eligibility

To comply with the strict terms of our public funding body, all applicants must meet the following baseline criteria:

• Sovereignty Status: Candidates must possess an absolute, unrestricted right to work in the UK (UK Nationals preferred). We cannot offer visa sponsorship or international remote working arrangements for these fixed-term packages.

• Geographic Restriction: Every hour of work, line of code, and data annotation must be executed strictly on UK soil. Working from overseas (including temporary remote working holidays) is contractually prohibited.

How to Apply

If you are ready to deliver a critical work package for this high-velocity technical automation project starting 1 July 2026, please submit your CV and a brief summary of your technical background. Please explicitly state your eligibility to work under UK Sovereignty Status guidelines.