Time since we first saw it
Day 12
Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
London, England, United Kingdom
Likely evergreen, first seen by us 12 days agoWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
You'll work on large-scale machine learning systems powering personalised outfit recommendations, style discovery and intelligent product experiences across the customer journey.
Our mission is to help millions of customers discover complete outfits that reflect their personal style, preferences and the latest fashion trends. Sitting within ASOS's Search & Discovery organisation, the team combines recommendation systems, personalisation, deep learning and emerging AI technologies to create new ways for customers to discover fashion beyond traditional ecommerce experiences. You'll work on large-scale machine learning systems powering personalised outfit recommendations, style discovery and intelligent product experiences across the customer journey. From recommendation and retrieval systems to deep learning and generative AI applications, you'll help bring innovative ideas into production and deliver experiences used by millions of customers. Working alongside Machine Learning Scientists, Software Engineers and Product Managers, you'll play a key role in designing, building and operating production ML systems at scale. You'll tackle challenging problems across recommendation systems, personalisation, deep learning and AI-powered outfit generation, helping shape the future of machine learning at ASOS.
Experience designing, building and deploying machine learning systems in production environments.
Strong understanding of machine learning engineering principles and modern software engineering practices.
Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow or similar.
Experience training and optimising models using large datasets and distributed compute infrastructure.
Experience working with recommendation systems, ranking, retrieval, personalisation or related machine learning domains.
Knowledge of MLOps practices, including model deployment, monitoring and lifecycle management.
Likely evergreenReposted 3 times since Sep 9, 2026. A role that keeps coming back is often kept open to collect applications rather than to fill one seat.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
Day 12
Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
13 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Strong understanding of machine learning engineering principles and modern software engineering practices. - Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow or similar. - Experience training and optimising models using large datasets and distributed compute infrastructure.
Complete your application on jobs.smartrecruiters.com. The employer’s form will show what is required.
Already applied? Track this application
Yes. We’ve followed 2 other Senior Machine Learning Engineer (Recommendations/Search) jobs there since September 2026. 2 came down, usually after about 16 days.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
We're looking for a Senior Machine Learning Engineer to join our Search and Recommendations team, where we're building the next generation of AI-powered fashion experiences at ASOS.
Our mission is to help millions of customers discover complete outfits that reflect their personal style, preferences and the latest fashion trends. Sitting within ASOS's Search & Discovery organisation, the team combines recommendation systems, personalisation, deep learning and emerging AI technologies to create new ways for customers to discover fashion beyond traditional ecommerce experiences.
You'll work on large-scale machine learning systems powering personalised outfit recommendations, style discovery and intelligent product experiences across the customer journey. From recommendation and retrieval systems to deep learning and generative AI applications, you'll help bring innovative ideas into production and deliver experiences used by millions of customers.
Working alongside Machine Learning Scientists, Software Engineers and Product Managers, you'll play a key role in designing, building and operating production ML systems at scale. You'll tackle challenging problems across recommendation systems, personalisation, deep learning and AI-powered outfit generation, helping shape the future of machine learning at ASOS.
What you’ll be doing:
About You
We're interested in candidates who bring experience in several of the following areas. We recognise that skills and expertise can be developed through a variety of experiences and career paths.
BeneFITS’
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.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
London, England, United Kingdom
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.