Senior Machine Learning Engineer (Personalisation)

Skills this role screens for

About the role

We're looking for a Senior Machine Learning Engineer to join our Search & Recommendations team, where we're building the machine learning systems that help millions of customers discover products every day.

Sitting within ASOS's Search & Recommenders area, the team is responsible for the recommendation, ranking and personalisation systems that sit at the heart of the customer journey. From surfacing the most relevant products and outfits to powering personalised shopping experiences, our work directly influences how customers discover and shop fashion on ASOS.

You'll work on large-scale machine learning systems that power experiences such as Similar Items, People Also Viewed and personalised customer journeys that adapt in real time. Leveraging signals from millions of customer interactions, we use recommendation systems, ranking models, deep learning and emerging AI technologies to connect customers with the products they're most likely to love.

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 Applied Scientists, Machine Learning Engineers, Software Engineers and Product Managers, you'll help turn innovative ideas into reliable, high-performing systems that deliver measurable customer and commercial impact.

This is an opportunity to tackle challenging problems across recommendation systems, search, ranking, personalisation and deep learning, while helping shape the future of machine learning at ASOS.

The work

What you'll be doing

• Work as part of a cross-functional team designing, building and improving machine learning systems that power search, ranking and recommendation experiences.
• Collaborate closely with Applied Scientists and engineers to develop and deploy machine learning solutions that deliver measurable customer and commercial value.
• Build, deploy and maintain batch and real-time machine learning models in production environments.
• Contribute to recommendation, ranking and personalisation capabilities that support millions of customer interactions each day.
• Continuously improve our systems, codebase and engineering practices while contributing ideas for new features and capabilities.
• Support and mentor other engineers through coaching, knowledge sharing and technical collaboration.
• Contribute to the team's technical direction and help evolve machine learning standards, best practices and ways of working across the wider ML community.

Who they want

About You

We're interested in candidates who bring experience in several of the following areas. You'll likely be someone who enjoys combining strong software engineering fundamentals with machine learning expertise and is excited by the challenge of building reliable, scalable systems that deliver real-world impact.

You may come from a recommendation systems, search, ranking, personalisation, deep learning or broader machine learning background. Most importantly, you'll enjoy solving complex technical problems, collaborating across disciplines and helping bring machine learning products from experimentation into production.

• Experience applying machine learning and deep learning techniques in production environments.
• Experience using deep learning frameworks and distributed computing technologies to build and deploy large-scale machine learning models.
• Experience working with distributed training infrastructure, GPU-based training environments and parallelisation approaches.
• Strong understanding of software engineering principles, development lifecycles and MLOps practices.
• Experience developing reliable, scalable machine learning systems in production.
• Comfortable providing technical leadership, mentoring and support to other engineers.
• Strong collaboration and communication skills, with the ability to work effectively across engineering, science and product teams.

What you get

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