Senior Machine Learning Engineer (Recommendations/Search)

Senior Machine Learning Engineer (Recommendations/Search)

Full-Time 63000 - 77000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Design and build AI-powered fashion experiences for millions of customers.
  • Company: Join ASOS, a leading online fashion retailer with a vibrant culture.
  • Benefits: Enjoy employee discounts, flexible benefits, and 25 days annual leave.
  • Other info: Be part of an inclusive team that values creativity and personal growth.
  • Why this job: Shape the future of fashion tech while working with cutting-edge AI technologies.
  • Qualifications: Experience in machine learning systems and strong collaboration skills required.

The predicted salary is between 63000 - 77000 £ per year.

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 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.

Qualifications

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 Py Torch, Tensor Flow 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.
  • Additional Information
  • Bene FITS’
  • 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
  • #J-18808-Ljbffr

Senior Machine Learning Engineer (Recommendations/Search) employer: ASOS

ASOS, the parent company of TOPSHOP and TOPMAN, is an exceptional employer that fosters a vibrant and inclusive work culture in the heart of London. With a strong commitment to employee growth, you will benefit from personalised learning opportunities and a supportive environment that encourages creativity and innovation. Enjoy competitive benefits such as generous annual leave, private medical care, and exclusive employee discounts, all while being part of a dynamic team dedicated to shaping the future of fashion.

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Contact Details:

ASOS Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Machine Learning Engineer (Recommendations/Search)

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at ASOS or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to ASOS.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like ASOS.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like ASOS that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Senior Machine Learning Engineer (Recommendations/Search)

Machine Learning Engineering
Deep Learning Frameworks (PyTorch, TensorFlow)
Model Deployment
MLOps Practices
Recommendation Systems
Personalisation Techniques
Cloud Services

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at ASOS.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at ASOS and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at ASOS

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If ASOS uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.