Machine Learning Engineer - Computer Vision
Addition
- London, England, United Kingdom
- London, England, United Kingdom
Über
Machine Learning Engineer
specialising in
Computer Vision
to help scale our clients vision AI product into a high-performing, reliable, production-ready platform.
Role Lead CV Model Development
– Design, train, and optimise detection, recognition, segmentation, and tracking models, balancing accuracy, speed, and robustness for real-world retail environments. Enhance synthetic data pipelines to improve generalisation and domain adaptation.
Advance Large Vision Models (LVM)
– Improve performance, scalability, and adaptability of our in-house LVM for diverse retail use cases.
Deliver Proven Solutions
– Experiment rapidly using PyTorch. Contribute to benchmarking and ongoing improvements.
Collaborate Across Teams
– Work with Product, Infrastructure, and Customer teams to integrate models into workflows. Provide technical leadership aligned with business goals.
Champion Data & MLOps
– Maintain high data quality standards and develop scalable automation systems for seamless deployment and experimentation.
Requirements PhD (or equivalent) in Computer Vision, Machine Learning, or related field.
Proven record deploying large-scale CV models in production.
Strong Python skills with PyTorch or TensorFlow expertise.
This is an excellent opportunity for an experienced Machine Learning Engineer to join a leading company that are driven towards success!
For further information on this Machine Learning Engineer position, apply below!
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
By applying you are confirming you are happy to be added to the Addition Solutions mailing list regarding future suitable positions. You can opt out of this at any time simply by contacting one of our consultants.
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Sprachkenntnisse
- English
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