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Machine learning engineer – computer vision focus

Slough
Brio Digital
Machine learning engineer
Posted: 21 June
Offer 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.

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