Machine Learning Engineer

We’re ASOS, the online retailer for fashion lovers all around the world.
We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions.
But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list.
Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you.
Job Description

We are seeking a

Machine Learning Engineer

with a strong foundation in deep learning to join a cross‑functional team. You'll work closely with data scientists and engineers to deliver impactful machine learning solutions across a wide range of data‑rich challenges.
In this role, you'll contribute to developing and deploying advanced algorithms that influence key areas like pricing strategies and personalised customer targeting, all at enterprise scale.
Key Responsibilities
Collaborate with cross‑functional teams to design, implement, and optimise machine learning models for real‑world business use cases.
Deploy and maintain both batch and real‑time machine learning systems at scale.
Work alongside data scientists to translate experimental models into robust production‑ready solutions.
Continuously improve model accuracy, system efficiency, and platform capabilities.
Contribute to defining team best practices and engineering standards in machine learning development.
Stay up to date with the latest industry research and bring new insights to the wider ML community within the business.
Qualifications

About You
Hands‑on professional experience in developing and deploying machine learning solutions, with a focus on deep learning.
Experience working with modern ML frameworks and familiarity with end‑to‑end deployment workflows.
Proficiency in training models using GPUs, and a strong interest in distributed computing and scalable systems.
Familiar with software development practices including version control, CI/CD, containerisation, and monitoring,especially within ML Ops workflows.
A collaborative mindset with strong communication skills and the ability to work effectively across multidisciplinary teams.
Motivated self‑starter with a desire to learn, share knowledge, and grow in a fast‑paced environment.
Additional Information

Competitive salary and performance‑based bonus scheme
Generous employee discount and exclusive product access
Structured personal and professional development opportunities
Paid annual leave plus an additional day for special personal milestones
Flexible benefits allowance and private medical care options
Access to a variety of online learning resources and employee‑led communities
A supportive, inclusive, and dynamic workplace where innovation thrives
Job Location
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