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For Companies At a Glance
- Tasks: Design and deploy cutting-edge machine learning models for image and video processing.
- Company: Join a top-tier client known for innovation in technology and data solutions.
- Benefits: Enjoy hybrid working, flexible hours, and opportunities for contract extensions.
- Why this job: Be at the forefront of AI technology while collaborating with talented professionals.
- Qualifications: Strong experience in Computer Vision, Python, and ML frameworks required.
- Other info: This is a 6-month contract with potential for further extensions.
The predicted salary is between 48000 - 72000 £ per year.
Job Description
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
Network with professionals in the machine learning and computer vision fields. Attend meetups, webinars, or conferences to connect with industry experts and learn about potential job openings that may not be advertised.
✨Tip Number 2
Showcase your projects on platforms like GitHub or personal websites. Highlight any machine learning models you've built, especially those related to computer vision, to demonstrate your hands-on experience and technical skills.
✨Tip Number 3
Stay updated with the latest trends and advancements in computer vision and deep learning. Follow relevant blogs, podcasts, and research papers to discuss these topics during interviews, showing your passion and commitment to the field.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and system design questions related to machine learning. Focus on problems involving CNNs, object detection, and model deployment to align with the job requirements.
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 well as any relevant cloud platform experience.
Craft a Strong Cover Letter: In your cover letter, emphasise your problem-solving skills and ability to work collaboratively in a hybrid environment. Mention any experience you have with MLOps tools and how you stay updated with advancements in deep learning and computer vision.
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 demonstrate your hands-on experience.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors. Ensure that all technical terms are used correctly and that your application is clear and professional.
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 a collaborative environment.
✨Highlight Your Experience with MLOps
Since the role involves deploying ML models into production, make sure to talk about your familiarity with MLOps tools like MLflow, Docker, or Kubernetes. Discuss any relevant experiences that showcase your ability to ensure scalability and reliability.
✨Stay Updated on Industry Trends
Demonstrating your knowledge of the latest advancements in deep learning and computer vision can set you apart. Be prepared to discuss recent developments or technologies that excite you, especially those related to transformer-based models or real-time inference.
