Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and run machine learning systems for personalised fashion experiences.
- Company: Join a leading fashion tech company with a focus on innovation.
- Benefits: Enjoy employee discounts, flexible benefits, and 25 days annual leave.
- Other info: Collaborative environment with opportunities for mentorship and career growth.
- Why this job: Make a real impact on customer experiences through cutting-edge machine learning.
- Qualifications: Experience in machine learning, especially deep learning and recommendation systems.
The predicted salary is between 60000 - 80000 £ per year.
We are 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:
- 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.
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.
Senior Machine Learning Scientist (Personalisation) employer: asos.com Ltd
Contact Detail:
asos.com Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Scientist (Personalisation)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working at ASOS or similar companies. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those related to personalisation or recommendation systems. This will help you stand out and demonstrate your expertise.
✨Tip Number 3
Prepare for technical interviews by brushing up on your deep learning techniques and MLOps practices. Practice coding challenges and be ready to discuss your past experiences in deploying machine learning models.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team and contributing to our mission of enhancing customer experience.
We think you need these skills to ace Senior Machine Learning Scientist (Personalisation)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Scientist role. Highlight your experience with machine learning systems, especially in personalisation, and don’t forget to mention any relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how you can contribute to our mission at StudySmarter. Be sure to mention your collaborative spirit and any mentoring experience you have.
Showcase Your Technical Skills: In your application, be specific about the technologies and frameworks you’ve worked with. Mention your experience with deep learning, recommendation systems, and any MLOps practices you’re familiar with. We love seeing candidates who are eager to learn and grow!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we can’t wait to see what you bring to the table!
How to prepare for a job interview at asos.com Ltd
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning knowledge, especially deep learning techniques and recommendation systems. Be ready to discuss your past experiences in production environments and how you've tackled challenges in deploying models at scale.
✨Show Off Your Collaboration Skills
Since this role involves working closely with engineers and data scientists, be prepared to share examples of how you've successfully collaborated in cross-functional teams. Highlight any projects where you contributed to shared goals or mentored junior team members.
✨Get Familiar with the Tech Stack
Do some homework on the modern deep learning frameworks and MLOps practices mentioned in the job description. If you have experience with CI/CD, containerisation, or observability, make sure to bring that up during the interview to show you're a good fit.
✨Ask Thoughtful Questions
Prepare some insightful questions about the company's approach to personalisation and how they use machine learning to enhance customer experience. This shows your genuine interest in the role and helps you understand if it's the right fit for you.