249 Medical Image Analysis jobs in the United Kingdom

6 Month Contract - Hybrid Working - Asap Start - Outside of IR-35

Overview

The Explore Group are working with one of our tier 1 clients in securing an experienced Machine Learning Engineer with strong expertise in Computer Vision to join our team on a 6 month initial contract (with guaranteed extensions). You will play a key role in designing, building, and deploying machine learning models that drive innovation in image and video processing.

Responsibilities

• Develop, train, and optimise computer vision models for real world applications.
• Work with large datasets including images and video, ensuring data preprocessing, augmentation, and pipeline optimisation.
• Deploy ML models into production, ensuring scalability, efficiency, and reliability.
• Collaborate closely with data scientists, software engineers, and product teams to translate business needs into technical solutions.
• Stay up to date with the latest advancements in deep learning, computer vision, and related technologies.

Key Skills & Experience

• Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow).
• Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn).
• Proven track record of building and deploying ML models in production environments.
• Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or similar).
• Experience working with cloud platforms (AWS, Azure, or GCP).
• Solid understanding of CNNs, object detection, segmentation, and image classification.
• Strong problem-solving skills and ability to work in a hybrid, collaborative environment.

Nice to Have

• Experience with transformer-based vision models (ViT, CLIP, SAM).
• Familiarity with real-time inference and optimisation (ONNX, TensorRT).
• Previous work on video analytics, 3D vision, or multi-modal ML projects.

• Design, train, and deploy advanced machine learning models for computer vision tasks, including image classification, object detection, segmentation, and tracking.
• Develop and optimize deep learning architectures (CNNs, Transformers, etc.) for real-time applications.
• Implement and manage end-to-end ML pipelines, from data preprocessing and feature engineering to model evaluation and deployment.
• Collaborate with software engineers to integrate ML models into production systems and applications.
• Conduct rigorous experimentation, benchmarking, and performance analysis of various ML algorithms and techniques.
• Stay abreast of the latest research and advancements in machine learning, deep learning, and computer vision.
• Mentor junior engineers and contribute to the team's technical growth and knowledge sharing.
• Evaluate and select appropriate tools, frameworks, and libraries for ML development (e.g., TensorFlow, PyTorch, OpenCV).
• Contribute to the architectural design and strategic direction of our AI initiatives.
• Ensure the scalability, robustness, and efficiency of deployed ML solutions.

• M.S. or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• 5+ years of hands-on experience in machine learning engineering, with a strong focus on computer vision.
• Proven track record of developing and deploying production-level computer vision models.
• Expertise in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Strong programming skills in Python, with experience in relevant libraries (NumPy, Pandas, Scikit-learn).
• Proficiency in computer vision libraries like OpenCV.
• Experience with data augmentation, model optimization, and transfer learning techniques.
• Solid understanding of algorithms, data structures, and software engineering best practices.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration abilities.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps principles is a plus.

• Develop and implement state-of-the-art machine learning models for computer vision tasks, including object detection, image segmentation, facial recognition, and pose estimation.
• Design, train, and fine-tune deep learning architectures (e.g., CNNs, RNNs, Transformers) using large datasets.
• Process and prepare image and video data for model training and evaluation.
• Evaluate model performance, conduct rigorous testing, and optimise models for accuracy, efficiency, and scalability.
• Collaborate closely with software engineers and product managers to integrate AI models into production systems.
• Stay current with the latest research and advancements in AI, machine learning, and computer vision.
• Contribute to the development of new AI-driven features and products.
• Write clean, efficient, and well-documented code in Python or other relevant programming languages.
• Participate in code reviews and contribute to technical discussions within the team.
• Troubleshoot and resolve technical challenges related to AI model development and deployment.

• Master's or PhD degree in Computer Science, Electrical Engineering, Artificial Intelligence, or a related quantitative field.
• 3-5 years of hands-on experience in developing and deploying machine learning models, with a strong focus on computer vision.
• Proficiency in Python and relevant ML/deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Solid understanding of image processing techniques and computer vision principles.
• Experience with deep learning architectures commonly used in computer vision.
• Familiarity with data augmentation techniques and strategies for handling imbalanced datasets.
• Experience with cloud computing platforms (AWS, Azure, GCP) and MLOps practices is a plus.
• Strong analytical, problem-solving, and critical-thinking skills.
• Excellent communication and teamwork abilities.
• A passion for innovation and a desire to work on challenging AI problems.

• Researching, designing, and implementing state-of-the-art computer vision algorithms.
• Developing and training deep learning models using large-scale datasets.
• Evaluating model performance, identifying areas for improvement, and implementing optimizations.
• Deploying ML models into production environments, ensuring scalability and reliability.
• Collaborating with cross-functional teams, including software engineers and product managers, to integrate AI capabilities into our products.
• Staying abreast of the latest advancements in AI, machine learning, and computer vision.
• Mentoring junior engineers and contributing to the team's technical growth.
• Working with cloud platforms (AWS, Azure, GCP) for model training and deployment.

Job title: Machine Learning Engineer

Locations: Manchester or Haywards Heath (hybrid working)

Role overview

Markerstudy Group have an exciting opportunity for a machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy’s market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment.

Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy’s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.

As a Machine Learning Engineer, you will help build and maintain the pricing team’s MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function.

Key Responsibilities:

• Build an MLOps / DevOps environment to support machine learning automation
li>Build the pipelines that automate the regular model update and monitoring processes
• Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes.
• Work closely with the data science team to integrate modelling approaches and techniques

Key Skills and Experience:

• Previous experience as a DevOps / MLOps engineer
• Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud)
• Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and modelling – from the ground-up, not only through the use of packages and libraries
< i>Proficient at communicating results in a concise manner both verbally and written
• Previous industry experience in a STEM role or educated to the Master’s level in a STEM or DS / ML / AI or maths-based discipline.

Behaviours:

< i>Collaborative and team player
• Logical thinker with a professional and positive attitude
• Passion to innovate and improve processes
• Strong grasp of industry standards, and proficient in either Python, R, or both

Job title: Machine Learning Engineer

Locations: Manchester or Haywards Heath (hybrid working)

Role overview

Markerstudy Group have an exciting opportunity for a machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy’s market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment.

Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy’s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.

As a Machine Learning Engineer, you will help build and maintain the pricing team’s MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function.

Key Responsibilities:

• Build an MLOps / DevOps environment to support machine learning automation
li>Build the pipelines that automate the regular model update and monitoring processes
• Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes.
• Work closely with the data science team to integrate modelling approaches and techniques

Key Skills and Experience:

• Previous experience as a DevOps / MLOps engineer
• Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud)
• Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and modelling – from the ground-up, not only through the use of packages and libraries
< i>Proficient at communicating results in a concise manner both verbally and written
• Previous industry experience in a STEM role or educated to the Master’s level in a STEM or DS / ML / AI or maths-based discipline.

Behaviours:

< i>Collaborative and team player
• Logical thinker with a professional and positive attitude
• Passion to innovate and improve processes
• Strong grasp of industry standards, and proficient in either Python, R, or both

A PhD level Machine Learning Scientist is needed to join this amazing research team based near King’s Cross. This is a unique opportunity to work at the forefront of AI research, contributing to projects that push the boundaries of what’s possible in machine learning.

You will play a key role in designing, implementing, and advancing cutting-edge methods in:

• Reinforcement Learning (RL)
• Large Language Models (LLMs)
• Optimisation for Deep Learning

You’ll work alongside a team of world-class researchers, developing new approaches, publishing at top-tier venues, and translating research into impactful real-world applications.

Experience Required:

• A PhD in Machine Learning, Computer Science, Mathematics, Physics, or a related field
• A track record of publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, ACL) (This is essential)
• Deep expertise in at least one of: RL, LLMs, or large-scale Optimisation for deep learning
• Good programming skills in Python and experience with deep learning frameworks
• A passion for advancing AI research and contributing to the global ML community

Key selling points

• Work on cutting-edge AI challenges with a talented, multidisciplinary team
• Collaborate with leading academic and industry partners
• Access to high-performance computing resources
• Publish your work at the leading conferences
• VISA sponsorship available

If you’re driven by curiosity, thrive in a research-focused environment, and want to contribute to the next wave of AI innovation, then please apply today

A PhD level Machine Learning Scientist is needed to join this amazing research team based near King’s Cross. This is a unique opportunity to work at the forefront of AI research, contributing to projects that push the boundaries of what’s possible in machine learning.

You will play a key role in designing, implementing, and advancing cutting-edge methods in:

• Reinforcement Learning (RL)
• Large Language Models (LLMs)
• Optimisation for Deep Learning

You’ll work alongside a team of world-class researchers, developing new approaches, publishing at top-tier venues, and translating research into impactful real-world applications.

Experience Required:

• A PhD in Machine Learning, Computer Science, Mathematics, Physics, or a related field
• A track record of publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, ACL) (This is essential)
• Deep expertise in at least one of: RL, LLMs, or large-scale Optimisation for deep learning
• Good programming skills in Python and experience with deep learning frameworks
• A passion for advancing AI research and contributing to the global ML community

Key selling points

• Work on cutting-edge AI challenges with a talented, multidisciplinary team
• Collaborate with leading academic and industry partners
• Access to high-performance computing resources
• Publish your work at the leading conferences
• VISA sponsorship available

If you’re driven by curiosity, thrive in a research-focused environment, and want to contribute to the next wave of AI innovation, then please apply today