Level

ASOS

Senior Machine Learning Engineer (Recommendations/Search)

AI in this role

pytorchtensorflow
ml-ops

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.

We're looking for a Senior Machine Learning Engineer to join our Search and Recommendations team, where we're building the next generation of AI-powered fashion experiences at ASOS.

Our mission is to help millions of customers discover complete outfits that reflect their personal style, preferences and the latest fashion trends. Sitting within ASOS's Search & Discovery organisation, the team combines recommendation systems, personalisation, deep learning and emerging AI technologies to create new ways for customers to discover fashion beyond traditional ecommerce experiences.

You'll work on large-scale machine learning systems powering personalised outfit recommendations, style discovery and intelligent product experiences across the customer journey. From recommendation and retrieval systems to deep learning and generative AI applications, you'll help bring innovative ideas into production and deliver experiences used by millions of customers.

Working alongside Machine Learning Scientists, Software Engineers and Product Managers, you'll play a key role in designing, building and operating production ML systems at scale. You'll tackle challenging problems across recommendation systems, personalisation, deep learning and AI-powered outfit generation, helping shape the future of machine learning at ASOS.

What you’ll be doing:

  • Design, build and operate production machine learning systems that power outfit discovery and personalised fashion experiences.
  • Partner with Machine Learning Scientists to deploy deep learning models and deliver meaningful customer and business outcomes.
  • Deploy and optimise batch and real-time machine learning models serving millions of customers.
  • Contribute to systems that power recommendations, personalisation and AI-driven fashion discovery experiences across ASOS.
  • Improve system performance, reliability, observability and scalability across the machine learning lifecycle.
  • Contribute to technical design decisions, architecture discussions and engineering best practices.
  • Mentor and support other engineers through coaching, collaboration and knowledge sharing.
  • Help strengthen technical practices across the team and the wider machine learning community at ASOS.
  • Contribute to the development of shared machine learning capabilities, tools and best practices used across multiple teams.

About You

We're interested in candidates who bring experience in several of the following areas. We recognise that skills and expertise can be developed through a variety of experiences and career paths.

  • Experience designing, building and deploying machine learning systems in production environments.
  • Strong understanding of machine learning engineering principles and modern software engineering practices.
  • Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow or similar.
  • Experience training and optimising models using large datasets and distributed compute infrastructure.
  • Experience working with recommendation systems, ranking, retrieval, personalisation or related machine learning domains.
  • Knowledge of MLOps practices, including model deployment, monitoring and lifecycle management.
  • Experience building reliable, observable and scalable services in cloud environments.
  • Comfortable providing technical leadership and mentoring other engineers.
  • Strong collaboration and communication skills, with experience working in cross-functional product teams.
  • Curiosity about emerging AI technologies and the practical application of LLMs and generative AI in customer-facing products.

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 

How we rate this

Senior Machine Learning Engineer (Recommendations/Search) at ASOS rates 99 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsPyTorchTensorFlow

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. What are the limits of TensorFlow that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: ML Ops, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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