5,579 Machine Vision jobs in the United Kingdom
Machine Learning/Computer Vision
Posted 3 days ago
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Job Description
We have 1 position open in the broad areas of Machine Learning and Computer Vision with a focus on Vision and Language. The positions are part of the Future Interaction Research Programme. Our topics of interest include but are not limited to:
- Contrastively-trained and auto-regressive Vision & Language (e.g. CLIP, BLIP).
- Visual LLMs (e.g. LLaVA).
- Generative Models (e.g. Stable Diffusion and Auto-Regressive models).
- Efficient Architectures.
- Model Compression (distillation, quantization).
- Efficient Adaptation of Large Models.
Key Responsibilities:
- Conduct hands-on innovative research, including methodological conceptualization and implementation.
- Publishing at top venues: CVPR, ECCV, ICCV, ICLR, NeurIPS, ICML, EMNLP, ACL, TPAMI and IJCV.
- Contribute to the research agenda and directions within the center.
- Interact with product and engineering teams for the purpose of technology transfer.
Skills and Qualifications
Key Skills Required:
- Research experience in the fields of Computer Vision and/or Machine Learning.
- Familiarity with fast prototyping Deep Learning frameworks such as PyTorch.
- A track record of publishing at top-tier venues (e.g. CVPR, ECCV, ICCV, ICLR, NeurIPS, EMNLP, ACL, ICML, TPAMI and IJCV).
- Ability to communicate well and to collaborate with other group members.
Machine Learning Engineer (Computer Vision)
Posted 2 days ago
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Job Description
Your responsibilities will include designing, implementing, and optimising machine learning algorithms for image and video analysis. You will work with large datasets, perform feature engineering, train deep learning models (e.g., CNNs, Transformers), and evaluate their performance. Collaboration with software engineers and domain experts will be key to integrating these models into our client's products and platforms. The ideal candidate is passionate about pushing the boundaries of AI and has a proven ability to translate complex research into practical applications. We are looking for individuals who thrive in a dynamic, team-oriented environment and are eager to contribute to groundbreaking projects.
Key Responsibilities:
- Design, develop, and implement machine learning models for computer vision tasks such as object detection, image segmentation, facial recognition, and pose estimation.
- Process, clean, and augment large datasets of images and videos for model training.
- Train, fine-tune, and evaluate deep learning models using frameworks like TensorFlow, PyTorch, or Keras.
- Optimise model performance for efficiency, accuracy, and scalability, considering deployment constraints.
- Collaborate with data scientists, software engineers, and product managers to define project requirements and integrate ML solutions.
- Stay current with the latest research and advancements in computer vision and deep learning.
- Conduct experiments, document findings, and present results to technical and non-technical audiences.
- Contribute to the continuous improvement of our ML infrastructure and MLOps practices.
- Troubleshoot and debug ML models and pipelines.
Qualifications:
- Master's or PhD degree in Computer Science, Machine Learning, or a related quantitative field, or equivalent practical experience.
- Proven experience in developing and deploying computer vision models.
- Strong programming skills in Python and proficiency with relevant ML libraries (e.g., OpenCV, scikit-image).
- Hands-on experience with deep learning frameworks (TensorFlow, PyTorch).
- Solid understanding of machine learning theory, algorithms, and best practices.
- Experience with cloud platforms (AWS, Azure, GCP) for ML development is a plus.
- Excellent problem-solving, analytical, and critical thinking skills.
- Strong communication and teamwork abilities, effective in a hybrid work setting.
Machine Learning Engineer - Computer Vision
Posted 7 days ago
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Job Description
Responsibilities:
- Develop, train, and evaluate machine learning models for various computer vision applications.
- Implement and optimize deep learning algorithms for tasks such as image classification, object detection, and segmentation.
- Design and build robust ML pipelines for data preprocessing, model training, and deployment.
- Collaborate with researchers and engineers to define project requirements and translate them into technical solutions.
- Stay up-to-date with the latest research and advancements in computer vision and machine learning.
- Conduct experiments, analyse results, and present findings to technical and non-technical audiences.
- Optimise model performance for efficiency, accuracy, and scalability.
- Contribute to the development of intellectual property and research publications.
- Work within a remote, agile environment, actively participating in team discussions and code reviews.
- Ensure code quality, maintainability, and adherence to best practices.
- MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Proven experience in developing and deploying machine learning models, with a focus on computer vision.
- Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Keras, OpenCV).
- Strong understanding of deep learning architectures (CNNs, RNNs, Transformers).
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration skills, particularly in a remote setting.
- Ability to work independently and manage projects effectively.
Machine Learning Engineer - Computer Vision
Posted 13 days ago
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Job Description
Key Responsibilities:
- Design, implement, and deploy state-of-the-art computer vision models for tasks such as object detection, image segmentation, facial recognition, and video analysis.
- Develop and optimize deep learning architectures using frameworks like TensorFlow, PyTorch, or Keras.
- Process and manage large-scale image and video datasets, including data augmentation and annotation strategies.
- Collaborate with research scientists to translate novel algorithms into production-ready code.
- Develop robust pipelines for training, evaluating, and monitoring ML models.
- Work on optimizing model performance for various hardware platforms and deployment scenarios.
- Stay current with the latest advancements in computer vision and machine learning research.
- Contribute to the design and architecture of ML systems and infrastructure.
- Collaborate with software engineering teams to integrate ML models into larger applications.
- Document research findings, model designs, and implementation details.
- MSc or PhD in Computer Science, Machine Learning, Electrical Engineering, or a related quantitative field.
- 3+ years of professional experience in machine learning, with a strong focus on computer vision.
- Proficiency in Python and deep learning frameworks (e.g., TensorFlow, PyTorch).
- Solid understanding of image processing techniques and computer vision algorithms.
- Experience with data preprocessing, feature engineering, and model evaluation.
- Familiarity with cloud platforms (AWS, GCP, Azure) and ML deployment strategies.
- Strong software engineering skills, including version control (Git) and testing.
- Excellent analytical and problem-solving abilities.
- Strong communication and collaboration skills, with the ability to work effectively in a team environment.
Machine Learning Engineer - Computer Vision
Posted 14 days ago
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Job Description
Responsibilities:
- Design, implement, and train machine learning models for computer vision tasks (e.g., image classification, object detection, segmentation).
- Develop and optimize deep learning architectures using frameworks such as TensorFlow, PyTorch, or Keras.
- Process and manage large datasets of images and videos for model training and evaluation.
- Deploy computer vision models into production environments, ensuring scalability and performance.
- Collaborate with software engineers to integrate ML models into existing applications and platforms.
- Stay current with the latest research and advancements in computer vision and deep learning.
- Conduct experiments and analyze results to improve model accuracy and efficiency.
- Develop and implement robust testing and validation procedures for ML models.
- Work closely with product managers and stakeholders to understand project requirements and translate them into technical specifications.
- Troubleshoot and debug issues related to model performance and deployment.
- Contribute to the development of reusable ML libraries and tools.
- Maintain comprehensive documentation for models, code, and experiments.
- Present research findings and project progress to technical and non-technical audiences.
- Ensure ethical considerations and bias mitigation are addressed in model development.
- Optimize models for deployment on various hardware, including edge devices.
Qualifications:
- Master's or PhD in Computer Science, Electrical Engineering, AI, or a related quantitative field.
- Minimum of 3 years of experience in machine learning engineering, with a specialization in computer vision.
- Strong proficiency in Python and ML libraries (e.g., OpenCV, Scikit-learn).
- Hands-on experience with deep learning frameworks (TensorFlow, PyTorch).
- Solid understanding of image processing techniques and algorithms.
- Experience with data augmentation and dataset management.
- Familiarity with cloud platforms (AWS, Azure, GCP) and ML services.
- Knowledge of MLOps principles and tools is a plus.
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork abilities.
- Ability to work effectively in a collaborative, on-site environment.
- Experience with embedded systems or edge AI is desirable.
Join a leading-edge team pushing the boundaries of AI technology. Our client is located in the vibrant city of Sheffield, South Yorkshire, UK .
Machine Learning Engineer - Computer Vision
Posted 21 days ago
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Job Description
You will be instrumental in designing, developing, and deploying cutting-edge computer vision models and solutions that drive advancements in various applications. The ideal candidate will have a strong foundation in machine learning, deep learning, and a passion for solving complex visual recognition and analysis challenges.
Responsibilities:
- Develop and implement machine learning algorithms for computer vision tasks, including image classification, object detection, segmentation, and tracking.
- Build, train, and evaluate deep learning models using frameworks such as TensorFlow or PyTorch.
- Preprocess and augment large image and video datasets for model training.
- Optimise model performance for inference speed and accuracy on various hardware.
- Collaborate with software engineers to integrate ML models into production systems.
- Conduct research into state-of-the-art computer vision techniques and propose innovative solutions.
- Stay up-to-date with the latest advancements in AI, machine learning, and computer vision.
- Document research, experiments, and model development processes thoroughly.
- Work closely with product teams to understand requirements and translate them into technical solutions.
- Participate in code reviews and contribute to the team's best practices.
- Troubleshoot and debug ML pipelines and models.
- Experiment with different model architectures and hyperparameter tuning.
- Contribute to the development of MLOps pipelines for deployment and monitoring.
- Evaluate and select appropriate tools and technologies for ML projects.
- Present findings and project updates to technical and non-technical stakeholders.
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, AI, or a related quantitative field.
- 2+ years of professional experience in machine learning or computer vision.
- Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, OpenCV, Scikit-learn).
- Strong understanding of deep learning architectures (CNNs, RNNs, Transformers).
- Experience with image and video processing techniques.
- Familiarity with cloud platforms (AWS, Azure, GCP) for ML workloads.
- Solid grasp of data structures, algorithms, and software engineering principles.
- Excellent analytical and problem-solving skills.
- Good communication and teamwork abilities.
- Experience with MLOps practices is a plus.
- Ability to work on complex projects with minimal supervision.
- A keen interest in continuous learning and staying current in the field.
- Experience with data augmentation techniques.
- Understanding of model deployment strategies.
Machine Learning Engineer - Computer Vision
Posted 22 days ago
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Job Description
Developing and optimising deep learning architectures (e.g., CNNs, RNNs).
Working with large-scale image and video datasets.
Pre-processing and augmenting visual data for model training.
Collaborating with software engineering teams to deploy models into production.
Researching and staying up-to-date with the latest advancements in computer vision and ML.
Building robust and scalable ML pipelines.
Conducting experiments and analysing results to improve model performance.
Contributing to the company's intellectual property through patents and publications.
Troubleshooting and debugging ML models and systems. Qualifications: Master's or PhD in Computer Science, Electrical Engineering, AI, or a related field with a focus on Computer Vision or Machine Learning.
Proven experience (4+ years) in developing and deploying computer vision models.
Strong programming skills in Python and proficiency with ML frameworks like TensorFlow, PyTorch, or Keras.
Deep understanding of computer vision algorithms, techniques, and mathematics.
Experience with data augmentation, image processing, and feature extraction.
Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps practices.
Excellent problem-solving and analytical skills.
Strong communication and teamwork abilities. Join us and contribute to groundbreaking advancements in visual intelligence.
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Machine Learning Engineer - Computer Vision
Posted 23 days ago
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Job Description
As a Machine Learning Engineer, you will be involved in the entire model lifecycle, from data preprocessing and feature engineering to model training, evaluation, and deployment. You'll work with large image and video datasets, applying deep learning techniques to solve complex problems such as object detection, image segmentation, facial recognition, and image generation. Collaboration with software engineers and domain experts will be crucial to ensure seamless integration of ML models into our broader technology stack.
Key Responsibilities:
- Design, implement, and optimize machine learning models for computer vision tasks.
- Develop robust data pipelines for image and video data processing and augmentation.
- Train, evaluate, and fine-tune deep learning models using frameworks like TensorFlow or PyTorch.
- Deploy machine learning models into production environments, ensuring scalability and performance.
- Collaborate with cross-functional teams to define project requirements and deliver solutions.
- Stay current with the latest research and advancements in computer vision and machine learning.
- Conduct rigorous testing and validation of ML models to ensure accuracy and reliability.
- Contribute to the development of internal ML platforms and tools.
- Document code, experiments, and model performance thoroughly.
- Participate in code reviews and knowledge-sharing sessions.
- Master's degree or Ph.D. in Computer Science, AI, Machine Learning, or a related quantitative field.
- Proven experience in developing and deploying computer vision models.
- Strong proficiency in Python and relevant ML libraries (e.g., OpenCV, scikit-learn).
- Hands-on experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
- Solid understanding of computer vision algorithms and techniques.
- Experience with data preprocessing, augmentation, and feature engineering for image data.
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices is a plus.
- Excellent problem-solving skills and the ability to work effectively in a team.
- Strong communication skills to articulate complex technical concepts.
- Ability to commute to Reading, Berkshire, UK for hybrid working arrangements.
Lead Computer Vision Engineer (Machine Learning)
Posted 12 days ago
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Job Description
Computer Vision/Machine Learning Research Manager
Posted 6 days ago
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Job Description
Research Engineering Manager
Location - London / Hybrid (3 days onsite, 2 days remote)
What are we looking for:
MicroTECH Global are looking for unique people for a distinctive technology.
Are you a Research Engineering Manager, who has a passion for technology, with a love to lead cutting-edge new research ideas that shapes the future of Technology?
We are seeking a driven and experienced Technical Manager to lead our clients research group. You will guide groundbreaking research projects in areas such as video and point cloud compression, AI/ML Applications & algorithm optimization for both performance and visual quality.
About the company:
MicroTECH Global are working with a company who are at the forefront of parallel data compression, with deep expertise in AI, data compression & XR (extended reality) They have developed multiple award-winning software products that are transforming industries such as TV, Live event production, Entertainment, Social Networks, Media, Aerospace, Automotive & Gaming
They achieve their goals by keeping our innovation cycle as agile and flexible as possible, with continuously testing and challenging assumptions. Thanks to the unique technology within the in-house testing facilities, they quickly pass from ideas to implementations.
Responsibilities:
As a Research Engineering Manager, you will:
• Leadership: Manage the day-to-day activities of the Research Group, ensuring timely project delivery, team performance, and recruitment of top talent.
• People Development: Actively mentor and develop engineers through regular 1:1s, objective setting, feedback, and addressing any concerns.
• Technical Leadership: Lead the design of algorithms and software for data compression systems, guiding your team in developing cutting-edge solutions.
• Documentation: Create and maintain technical documentation, including project reports, white papers, and intellectual property (IP) capture
• Process Improvement: Continuously enhance the Research Group’s processes and tools, driving efficiency and quality across the department.
Background and Experience:
• Passion for Research: A deep enthusiasm for advancing research in a dynamic environment.
• Pragmatism: A passion for hypothesis-driven innovation, enabling rapid cycles of iteration and fast-tracked delivery of Minimum Viable Products.
• Technical Expertise: Experience in designing and developing data compression solutions, AI/ML technologies, and/or C++ development.
• Leadership Skills: Proven ability to manage and mentor a skilled team, driving projects to completion within commercial deadlines.
• Communication Skills: Excellent written and verbal communication, including technical documentation and project reporting.
• Flexibility: Ability to thrive in an innovative, cross-functional environment where initiative and adaptability are key.
• Deep understanding of data compression technologies, including lossy/lossless compression, quality metrics, and colour spaces.
• Knowledge of the end-to-end software development lifecycle, with experience collaborating across teams.
• Proficiency in Python and C++ software development.
• Experience with parallel processing programming.
• Understanding of standardization processes and standard-developing organizations (SDOs).
Beneficial to have:
• Knowledge of objective Visual Quality (VQ) assessment techniques.
• Experience with TensorFlow, visual AI (e.g., media indexing), and/or multimodal Generative AI.
• Experience in Intellectual Property development.
• Experience presenting research findings at conferences and within video-centric forums.
• Contribution to standard-developing organizations (SDOs).
• Experience with Agile development methodologies and tools like JIRA.
• Proficiency in software development tools such as GIT.