Machine Learning Engineer (hybrid or remote)

{ “@context”: “http://schema.org”, “@type”: “JobPosting”, “title”: “Machine Learning Engineer (hybrid or remote)”, “description”: “Machine Learning Engineer (Computer Vision) Location: Surrey or Bristol (hybrid) Type: Permanent (full-time) Team: AI / Computer Vision We're a UK-based technology business building AI-led vision systems that turn image and video streams into automated, real-time insight . Our products are used in operational environments where speed, reliability, and accurate detection matter-helping teams monitor large areas and respond quickly when something changes. We're looking for a Machine Learning / Computer Vision Engineer to help tackle challenging real-world problems using modern deep learning. You'll work closely with a multidisciplinary team to develop, productionise, and deploy computer vision models that run reliably across cloud and edge environments. Build, test, and improve production-grade deep learning models for computer vision tasks (classification, detection, segmentation, tracking) Optimise and deploy CV/ML pipelines to cloud and edge platforms Design, curate, and manage image/video datasets for training and evaluation Create synthetic data pipelines (including generative approaches) to augment real-world datasets Stay current with emerging tools, methods, and best practices in CV/ML Degree in Computer Science, Electrical Engineering, Robotics (or similar), or equivalent commercial experience Strong, production-ready Python engineering (version control, testing, code reviews) Experience with real-world sensor data (e.g., Model optimisation/deployment tooling (ONNX, TensorRT) Edge deployment experience (e.g., Relevant open-source contributions in computer vision”, “datePosted”: “2026-05-22”, “hiringOrganization”: { “@type”: “Organization”, “name”: “Matchtech”, “sameAs”: “https://uk.whatjobs.com/pub_api__cpl__439418926__4861?utm_campaign=publisher&utm_medium=api&utm_source=4861&geoID=22” }, “jobLocation”: { “@type”: “Place”, “address”: { “@type”: “PostalAddress”, “addressLocality”: “Bristol” } } }