At a Glance
- Tasks: Design and build AI-powered fashion experiences with cutting-edge machine learning systems.
- Company: Join ASOS, a leader in innovative fashion technology.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative environment with mentorship opportunities and career advancement.
- Why this job: Make a real impact on how millions discover their personal style.
- Qualifications: Experience in machine learning and a passion for fashion technology.
The predicted salary is between 60000 - 80000 £ per year.
We're looking for a Senior Machine Learning Engineer to join our cross-functional Outfits Discovery 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 match their personal style, preferences and the latest fashion trends.
We develop large-scale machine learning systems that power personalised outfit recommendations, style discovery and intelligent product experiences across the customer journey.
As a Senior Machine Learning Engineer, you'll play a key role in designing, building and operating production machine learning systems at scale.
Working alongside Machine Learning Scientists, Software Engineers and Product Managers, you'll help turn cutting-edge research into robust, customer-facing solutions that drive measurable impact for both our customers and the business.
This is an opportunity to work on challenging problems spanning recommendation systems, deep learning, personalisation and large-scale inference, while helping shape the technical direction of machine learning across ASOS.
What you'll be doing
- Designing, building and operating production‑grade machine learning systems that power outfit discovery and personalised fashion experiences.
- Partnering with Machine Learning Scientists to productionise deep learning models and deliver measurable customer and business impact.
- Deploying and optimising batch and real‑time machine learning models that serve millions of customers at scale.
- Driving improvements in system performance, reliability, observability and scalability across the machine learning lifecycle.
- Taking ownership of technical design decisions and contributing to the team's architecture, standards and engineering practices.
- Mentoring and supporting other engineers, helping raise the technical bar across the team and wider machine learning community at ASOS.
- Contributing to the development of shared machine learning capabilities, tools and best practices used across multiple teams.
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StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer
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We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at asos.com Ltd, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at asos.com Ltd. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at asos.com Ltd
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
