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Open nowPosted 5 hours ago

Senior Machine Learning Scientist (Personalisation)

ASOS68 open roles

Where
London, England, United Kingdom
Work mode
Hybrid
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Your applicationOpen nowSenior Machine Learning Scientist (Personalisation)ASOS · London, England, United Kingdom
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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. ASOS postings stay open a median of 18 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted 5 hours ago

ASOS median: 18 days open

The posting

Company Description

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.

Job Description

We’re looking for a Senior Machine Learning Engineer to join our cross‑functional Personalisation team. In this role, you’ll help design, build and run machine learning systems that enable customers to discover and shop outfits that reflect their personal style as well as current fashion trends.

This is a senior individual contributor role where you’ll work closely with engineers, data scientists and product partners to productionise machine learning at scale. Our mission is to continuously improve the customer experience through thoughtful, responsible and high‑impact use of machine learning.

What you’ll be doing

  • Working as part of an agile, cross‑functional team to build and improve algorithms used in areas such as pricing and customer targeting
  • Collaborating with scientists and engineers to implement and deploy machine learning solutions at scale, supporting hundreds of millions of products and customers
  • Deploying and maintaining both batch and real‑time machine learning models in production environments
  • Improving and evolving our codebase, tooling and platforms, and contributing to the design of new features and capabilities
  • Supporting and mentoring more junior team members, helping them develop their technical skills and confidence
  • Contributing to technical direction, helping define machine learning standards, and sharing knowledge across ASOS’s wider ML and engineering community

Qualifications

About you:

  • Professional experience applying machine learning in real‑world, production environments, with a focus on deep learning techniques
  • Experience working with recommendation or ranking systems (or a strong interest in this space)
  • Familiarity with modern deep learning frameworks and distributed computing approaches for training large‑scale models
  • Experience training models across GPUs using data and/or model parallelism, or enthusiasm to deepen your knowledge in this area
  • A solid understanding of software engineering principles, including data pipelines, CI/CD, containerisation and observability, with exposure to MLOps practices and tooling
  • Comfortable providing technical guidance, mentoring and support to a small number of less‑experienced engineers
  • Enjoy collaborating across teams and contributing to shared engineering initiatives

Additional Information

BeneFITS’

  • 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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