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Day 6
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London, England, United Kingdom
Actively hiring, first seen by us 6 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
Design, build and operate ML systems for customer engagement, marketing and pricing
Own the end-to-end lifecycle of ML products, from data ingestion to monitoring
Turn Applied Scientists' research into scalable production systems
Build reusable tooling and infrastructure to speed up ML delivery
Influence technical direction and mentor colleagues on engineering quality
Design, build and operate machine learning systems that support customer engagement, marketing effectiveness, pricing and commercial decision-making.
Own the end-to-end engineering lifecycle of machine learning products, including data ingestion, feature engineering, deployment, monitoring and optimisation.
Partner closely with Applied Scientists to translate research and experimentation into scalable production systems.
Build reusable tooling, frameworks and infrastructure that accelerate machine learning delivery and reduce operational overhead.
Influence technical direction and architectural decisions across machine learning products and platforms.
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.
Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 6
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.
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- 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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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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