Senior Machine Learning Engineer (Customer/Marketing)

ASOS.com

Greater London

On-site

GBP 90,000 - 120,000

Full time

25 hours ago
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Benefits offered by this job

ASOS employee discount
Employee sample sales
25 days annual leave + extra day
Discretionary bonus
Private medical care
Flexible benefits allowance
Personalised learning opportunities

Job summary

ASOS.com is seeking a Senior Machine Learning Engineer to join the Customer & Martech team. You will design, build and scale ML systems that power customer growth, marketing effectiveness, pricing and personalisation, leveraging massive datasets across customer behaviour, transactions and product data.

You will work with Applied Scientists, Data Engineers and ML Engineers to take ML products from ideation to deployment, monitoring and optimisation at ASOS scale, shaping the next generation of ML

Qualifications

  • Experience deploying ML systems in production environments.
  • Strong Python and software engineering fundamentals.
  • Experience building scalable batch and real-time ML pipelines in cloud environments.
  • Solid understanding of MLOps: model deployment, monitoring, CI/CD, observability, operational excellence.
  • Experience with large-scale data processing technologies such as Spark.
  • Proficiency with ML frameworks like PyTorch or TensorFlow.
  • Experience designing reliable APIs/services for ML-powered products.
  • Ability to work through ambiguity and lead complex initiatives.
  • Experience in customer intelligence, marketing optimisation, pricing, forecasting or personalisation.
  • Experience building ML platforms or shared ML infrastructure.
  • Exposure to experimentation frameworks or causal inference.
  • Mentoring engineers and influencing technical direction beyond your team.
  • Track record of delivering ML solutions with measurable customer or commercial outcomes.

Responsibilities

  • Design, build and operate ML systems that support customer engagement, marketing effectiveness, pricing and decision-making.
  • Own end-to-end engineering lifecycle of ML products: data ingestion, feature engineering, deployment, monitoring and optimisation.
  • Productionise ML solutions and ensure reliable operation at ASOS scale.
  • Collaborate with Applied Scientists to translate research into scalable production systems.
  • Shape the future of the MLOps platform and improve engineering practices and platform capabilities.
  • Build reusable tooling, frameworks and infrastructure to accelerate ML delivery and reduce operational overhead.
  • Influence technical direction and architectural decisions across ML products and platforms.
  • Mentor colleagues and uphold high standards of engineering quality, reliability and scalability.

Skills

ML in production
Python programming
Cloud ML pipelines
MLOps
Spark
ML frameworks
API design
Ambiguity handling
Customer analytics
ML platforms
Experimentation/causal inference
Technical leadership

Job 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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