Machine Learning / Computer Vision Engineer – Data Scientist

CV-Library
Reading, Berkshire
14 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Rebel Recruitment Nottingham, Nottinghamshire, United Kingdom
£500 – £600 pd Hybrid

Data Scientist / AI Engineer

Searchability NS&D Cheltenham, United Kingdom
£45,000 – £95,000 pa On-site Clearance Required

Machine Learning Software Engineer, Research

PhysicsX London, United Kingdom
£50,000 – £90,000 pa On-site

Staff Machine Learning Software Engineer, Research

PhysicsX London, United Kingdom
£70,000 – £120,000 pa On-site

Senior Computer Vision Data Scientist

PhysicsX North Tyneside, NE29 8EP, United Kingdom
£120,000 – £160,000 pa On-site

Data Science Manager

Technify Talent Limited Reading, Berkshire, United Kingdom
£90,000 – £100,000 pa Hybrid
Posted
11 Mar 2025 (14 months ago)

Machine Learning / Computer Vision Engineer – Data Scientist – Remote (UK only)

I’m working with a rapidly growing tech company in Berkshire to recruit a Data Scientist / Machine Learning Engineer to join their team. They are particularly interested in someone with a strong academic background in Computer Vision and Deep Learning. Joining their Data Science team this will be a pivotal role on their Machine learning research and development initiatives and implementation, to solve complex business challenges through cutting-edge Machine Learning models and algorithm development.

Key Responsibilities

  • Develop advanced machine learning algorithms and statistical models to extract insights from complex datasets

  • Build and optimize state-of-the-art computer vision and deep learning models

  • Design and implement end-to-end machine learning pipelines from data collection to deployment

  • Conduct research into novel ML approaches and translate academic innovations into practical business applications

  • Implement data cleaning strategies, feature engineering, and synthetic data generation

  • Develop machine learning models that can handle real-world data constraints and limitations

  • Collaborate with cross-functional teams to define project requirements and technical strategies

  • Ensure models meet quality standards and performance metrics through rigorous validation techniques

    Required Qualifications

  • MSc or PhD in Machine Learning, Data Science, Computer Vision, Artificial Intelligence, Computer Science or related fields.

  • 3+ years of professional experience in Data Science/Machine Learning roles

  • Strong expertise in machine learning techniques including supervised and unsupervised learning, ensemble methods, and clustering

  • Experience with rule-based systems, fuzzy logic, and aggregation operators for information fusion

  • Deep expertise in computer vision techniques including image classification, object detection, and semantic segmentation

  • Strong programming skills in Python and experience with ML/DL frameworks (Scikit-Learn, PyTorch, TensorFlow)

  • Experience with cloud platforms and containerisation technologies

  • Excellent communication skills and ability to translate complex technical concepts for diverse audiences

    Technical Skills

  • Machine Learning: Classification, regression, clustering, ensemble models, information fusion, rule-based systems

  • Deep Learning Frameworks: PyTorch, TensorFlow 2, Keras

  • Computer Vision: Image classification, object detection, semantic segmentation, visual transformers, representation learning

  • Data Science Libraries: Scikit-Learn, NumPy, Pandas, Matplotlib, SciPy

  • Cloud & DevOps technologies

    What Sets You Apart

  • A strong academic background in Data Science, Machine Learning / Deep Learning

  • History of building production-ready Machine Learning / Computer Vision models that deliver business value

  • Strong understanding of both theoretical foundations and practical implementations of cutting-edge Machine Learning techniques

    Salary: £70,000 + benefits

    Location: Remote working (UK only)

    APPLY TODAY for immediate consideration and interview in the next week

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise AI Jobs in the UK (2026 Guide)

Advertising AI jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly informed and in demand across multiple sectors simultaneously. General job boards reach a broad audience but lack the specificity that AI professionals expect — and the filtering mechanisms they rely on. Specialist platforms, direct outreach and academic channels each serve a different part of the market. This guide, published by ArtificialIntelligenceJobs.co.uk, covers where to advertise AI roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about time-to-hire across different role types.

New AI Employers to Watch in 2026: UK and Global Companies Reshaping AI Careers

The artificial intelligence job market in the UK is evolving at an extraordinary pace. With record-breaking investment, government backing, and a surge in enterprise adoption, the landscape of AI employers is shifting rapidly. For candidates exploring opportunities on ArtificialIntelligenceJobs.co.uk, understanding who is hiring next is just as important as understanding what skills are in demand. In this article, we explore the new and emerging AI employers to watch in 2026, focusing on organisations that have recently secured funding, won major contracts, or expanded their UK footprint. From cutting-edge startups to global giants doubling down on Britain, these companies represent the next wave of AI career opportunities.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.