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ASOS

Senior Machine Learning Engineer

Location:  London, United Kingdom
Location flexibility:  3 office days / week – may vary across teams (tech teams 3 days at home)
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Job Description

Company Description

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.

Job Description

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:

  • 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.
  • Productionise advanced machine learning solutions and ensure they operate reliably at ASOS scale.
  • Partner closely with Applied Scientists to translate research and experimentation into scalable production systems.
  • Help shape the future of our MLOps platform by contributing to engineering best practices, operational excellence and platform capabilities.
  • 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.
  • Mentor colleagues and support high standards of engineering quality, reliability and scalability.

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.

Qualifications

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.

  • 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 designing reliable APIs, services and platforms that support machine-learning-powered products.
  • Ability to work through ambiguity and lead complex technical initiatives.
  • Experience in customer intelligence, marketing optimisation, pricing, forecasting or personalisation.
  • Experience building feature platforms, ML platforms or shared machine learning infrastructure.
  • Exposure to experimentation frameworks, causal inference or measurement platforms.
  • Experience mentoring engineers and influencing technical direction beyond your immediate team.
  • A track record of delivering machine learning solutions that generated measurable customer or commercial outcomes.

Additional Information

What's in it for you?

  • Employee discount (hello ASOS discount!)
  • Employee sample sales
  • 25 days paid annual leave + an extra celebration day for a special moment
  • Discretionary bonus scheme
  • Private medical care scheme
  • Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits
  • Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role
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Working at ASOS

3 office days / week – may vary across teams (tech teams 3 days at home)

A little flex time

Company benefits

25 days annual leave + bank holidays
401K
Accrued annual leave – Max 5 days to carry over
Adoption leave – 26 weeks enhanced pay
Annual bonus
Annual pay rises
Bike parking
Birthday off
Buy or sell annual leave
Cinema discounts
Coffee discounts
Company freebies
Compassionate leave
Critical Illness Insurance
Dental coverage
Early finish Fridays
Emergency leave
Employee assistance programme
Employee discounts
Enhanced maternity leave – 26 weeks enhanced pay
Enhanced paternity leave – 8 weeks enhanced pay
Enhanced pension match/contribution
Enhanced sick days
Enhanced sick pay
Eye Care Support
Faith rooms
Family health insurance
Fertility benefits
Financial coaching
Further education support
Gym membership
Hackathons
Health insurance
Hertility subscription
In house training
On-site catering
On-site massages
On-site workout classes
On-site yoga classes
Learning platform
Life assurance
Mental health first aiders
Mental health platform access – Access to EAP (Unum)
Mentoring
Neonatal leave – 16 weeks leave
On-site gym
On-site wellness room
Open to compressed hours
Open to part time work for some roles
Open to part-time employees
Personal development days
Pregnancy loss leave – 10 days paid leave
Private GP service
Professional subscriptions
Referral bonus
Religious celebration leave
Restaurant discounts
Sabbaticals
Salary sacrifice
Shared parental leave – 26 weeks enhanced pay
Skilled worker visas
Study support
Teambuilding days
Time off in-lieu
Travel loan
Volunteer days
Summer hours
Secure on-site parking
Modern office
Private booths
Collaboration spaces
On-site barista
On-site shower
On-site personal trainer
Carer’s leave
Fertility treatment leave
Women’s health leave
Menopause support

Awards & Accreditations

2nd – Most loved - Medium companies

2nd – Most loved - Medium companies

Flexa awards 2026
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Company employees:

3,000

Gender diversity (m:f):

35:65

Hiring in countries

United Kingdom

Office Locations