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Base pay range 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.
Seniority level Seniority levelMid-Senior level
Employment type Employment typeFull-time
Job function Job functionEngineering and Information Technology
IndustriesRetail
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