Time since we first saw it
Day 0
Early. Similar jobs usually come down between day 6 and day 70.
At ASOS, jobs usually come down by about day 10.
From 4,442 similar postings that came down, and 33 of ASOS’s. Coming down is not always a hire.
London, England, United Kingdom
Live, first seen by us todayWork 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
Experience building, deploying and operating machine learning systems in production environments.
Experience building scalable batch and real-time machine learning pipelines in cloud environments.
Strong understanding of MLOps principles, including model deployment, monitoring, CI/CD, observability and operational excellence.
Experience working with large-scale data processing technologies such as Spark.
Strong understanding of machine learning frameworks such as PyTorch, TensorFlow, XGBoost or similar technologies.
Experience designing reliable APIs, services and platforms that support machine-learning-powered products.
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 0
Early. Similar jobs usually come down between day 6 and day 70.
At ASOS, jobs usually come down by about day 10.
From 4,442 similar postings that came down, and 33 of ASOS’s. 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.
- Experience building, deploying and operating machine learning systems in production environments. - Strong software engineering fundamentals, including expertise in Python and modern engineering practices. - Experience building scalable batch and real-time machine learning pipelines in cloud environments.
- Strong understanding of MLOps principles, including model deployment, monitoring, CI/CD, observability and operational excellence. - Experience working with large-scale data processing technologies such as Spark. - Strong understanding of machine learning frameworks such as PyTorch, TensorFlow, XGBoost or similar technologies.
- Experience working with large-scale data processing technologies such as Spark. - Strong understanding of machine learning frameworks such as PyTorch, TensorFlow, XGBoost or similar technologies. - Experience designing reliable APIs, services and platforms that support machine-learning-powered products.
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Already applied? Track this application
Yes. We’ve followed one other Senior Machine Learning Engineer (Customer/Marketing) job there since October 2026. It came down after 7 days.
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
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.
At ASOS, machine learning is a core part of how millions of customers discover products, engage with our brand and shop every day.
We're looking for a Senior Machine Learning Engineer to join our Customer & Martech team. In this role, you'll help build and scale machine learning products that support customer growth, marketing effectiveness, pricing and personalisation.
You will work with some of ASOS's richest datasets, including customer behaviour, transactions, marketing interactions and product data, turning these into production-grade machine learning systems that deliver measurable value for customers and the business.
Working alongside Applied Scientists, Data Engineers and Machine Learning Engineers, you'll contribute across the full lifecycle of machine learning products, from ideation and experimentation through to deployment, monitoring and optimisation.
Whether improving customer retention, optimising marketing investment, supporting intelligent pricing decisions or helping build the next generation of customer experiences, you'll work on complex challenges at significant scale.
What you'll be doing:
This is an opportunity to work on machine learning products used by millions of customers, leveraging rich datasets across customer behaviour, marketing, pricing and ecommerce. You'll collaborate with Applied Scientists, Machine Learning Engineers and Data Engineers to solve complex challenges at the intersection of machine learning, software engineering and large-scale data systems, while seeing the direct impact of your work on customer experience and commercial outcomes. You'll also help shape the future of ASOS's machine learning platform and engineering standards in an environment where machine learning is a core business capability.
We recognise that people may not meet every requirement listed above. If your experience is relevant to the role and you believe you could contribute to the team, we encourage you to apply.
What's in it for you?
We're ASOS. We blend our flair for fashion with our love of cutting- edge technology, but more importantly were interested in how we can bring the best out of you.
We exist to give people 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 judgment, and channel your creativity into a platform used by millions.
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London, England, United Kingdom
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