Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design, build, and deploy cutting-edge machine learning models for image and video processing.
- Company: Join a tier 1 client known for driving innovation in technology.
- Benefits: Enjoy hybrid working, flexible hours, and guaranteed contract extensions.
- Why this job: Be at the forefront of AI technology while collaborating with top professionals in the field.
- Qualifications: Strong experience in Computer Vision, Python, and ML frameworks required.
- Other info: This is a 6-month contract with opportunities for growth and learning.
The predicted salary is between 48000 - 72000 £ per year.
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 optimisecomputer vision modelsfor 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.
Machine Learning Engineer - Computer Vision employer: Explore Group
Contact Detail:
Explore Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Computer Vision
✨Tip Number 1
Make sure to showcase your hands-on experience with Computer Vision frameworks like OpenCV, PyTorch, and TensorFlow. Highlight specific projects where you've successfully implemented these technologies, as this will demonstrate your practical skills to potential employers.
✨Tip Number 2
Familiarise yourself with MLOps tools such as MLflow, Kubeflow, Docker, and Kubernetes. Being able to discuss how you've used these tools in previous roles can set you apart from other candidates and show that you're ready for production environments.
✨Tip Number 3
Stay updated on the latest advancements in deep learning and computer vision. Follow relevant blogs, attend webinars, or join online communities. This knowledge will not only help you in interviews but also demonstrate your passion for the field.
✨Tip Number 4
Network with professionals in the machine learning and computer vision space. Attend meetups or conferences, and connect with people on platforms like LinkedIn. Building relationships can lead to referrals and insider information about job openings.
We think you need these skills to ace Machine Learning Engineer - Computer Vision
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with computer vision frameworks like OpenCV, PyTorch, and TensorFlow. Include specific projects where you've developed, trained, and deployed ML models, as this will demonstrate your hands-on expertise.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention your familiarity with MLOps tools and cloud platforms, and how your skills align with the responsibilities outlined in the job description.
Showcase Relevant Projects: If you have worked on projects involving CNNs, object detection, or video analytics, be sure to include these in your application. Provide links to your GitHub or portfolio to give tangible evidence of your capabilities.
Highlight Continuous Learning: Mention any recent courses, certifications, or workshops related to deep learning and computer vision that you've completed. This shows your commitment to staying updated with the latest advancements in the field.
How to prepare for a job interview at Explore Group
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with Computer Vision frameworks like OpenCV, PyTorch, and TensorFlow. Bring examples of projects where you've developed, trained, and optimised models, as this will demonstrate your practical knowledge.
✨Discuss Your Problem-Solving Approach
Employers are keen on understanding how you tackle challenges. Be ready to share specific instances where you've solved complex problems in machine learning or computer vision, particularly in production environments.
✨Highlight Collaboration Experience
Since the role involves working closely with data scientists and software engineers, emphasise your ability to collaborate effectively. Share examples of successful teamwork and how you translated business needs into technical solutions.
✨Stay Updated on Industry Trends
Demonstrate your passion for the field by discussing recent advancements in deep learning and computer vision. Mention any relevant research papers or technologies you've explored, especially those related to transformer-based models or real-time inference.