Senior Machine Learning Engineer (Recommendations)

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, with expertise in Machine Learning and Deep Learning to join our Search & Recommendations team, where we build the machine learning systems that help millions of customers discover products every day.

From personalised recommendations and product ranking to emerging AI-powered styling experiences, our work sits at the heart of the customer journey and directly influences how customers explore and shop on ASOS.

Our recommendation and ranking systems power experiences such as Similar Items, People Also Viewed, and personalised customer journeys that adapt in real time based on customer behaviour. These systems operate at significant scale, using signals from millions of interactions to surface the most relevant products and content.

As a Machine Learning Engineer, you'll work across the full machine learning lifecycle – from experimentation and model development through to deployment, monitoring and optimisation in production environments. You'll collaborate closely with Machine Learning Engineers, Applied Scientists, Software Engineers and Product partners to transform ideas into reliable, scalable systems that deliver measurable customer and commercial impact.

You will be a senior IC who will be productionising machine learning systems that help our customers discover and shop complete outfits that resonate with both their personal style and current fashion trends. Our mission is to elevate the fashion experience and ship with high scale ML capabilities.

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.
• 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.

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 range of experiences and career paths.

• 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.

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