Machine Learning Engineer - Computer Vision Focus...

Job Description Job Title: Machine Learning Engineer – Computer Vision Focus Overview: We’re looking for a skilled Machine Learning Engineer to join a growing technology company building cutting-edge solutions for real-world automation. You’ll be part of a small, collaborative team applying computer vision to improve performance, efficiency, and user experience across multiple sectors. This role offers the chance to work on high-impact machine learning problems, shape production-ready models, and contribute to the development of a platform that’s democratising access to AI-driven automation. Key Responsibilities: – Model Development: Design, train, and deploy machine learning models for computer vision use cases such as object detection, classification, and segmentation. – Data Handling: Collaborate with data engineers to manage large datasets, ensuring quality data pipelines for model training and evaluation. – Algorithm Tuning: Optimise model performance through experimentation with architectures and hyperparameters. – Cross-Functional Collaboration: Work closely with engineers, product managers, and designers to integrate ML solutions into customer-facing applications. – Monitoring & Maintenance: Maintain model performance in production, troubleshoot issues, and roll out updates as needed. – Research & Innovation: Keep current with advances in ML and CV, and apply new methods to solve business problems. Your Profile: – Master’s degree (or equivalent) in Computer Science, Machine Learning, or a related field. – 3+ years of experience deploying ML models in production. – Proficient in Python and ML frameworks (e.g., TensorFlow, PyTorch). – Experience working with cloud platforms and containerised deployments (e.g., Docker, Kubernetes). – Solid grounding in computer vision and experience with large-scale data. – Bonus: exposure to reinforcement learning methods. What’s on Offer: – Flexible Work Setup: Hybrid-first approach with the option to work remotely or from our London collaboration space. – Equity Options: Share in the company’s long-term success. – Time Off: Up to 34 days annual leave including UK public holidays. – Health & Wellbeing: Comprehensive private health cover (including mental health, dental, optics, and travel insurance). – Retreats & Team Events: Regular in-person team gatherings and an annual company-wide retreat. – Pension Scheme: Employer-supported contribution plan. – Culture: Inclusive, open-minded, and team-oriented working environment.