Senior Applied Scientist - Recommendations

Votre Sommelier; London; On-site; GBP 70,000 - 90,000; Full time

Job summary

A leading online fashion retailer is seeking a Senior Applied Scientist to enhance user experience through large-scale recommender systems. This hands-on role involves designing algorithms, mentoring peers, and collaborating with cross-functional teams to deliver impactful solutions.

Benefits

Competitive compensation package

Continuous learning and development resources

Flexible working arrangements

Paid annual leave

Employee perks including product discounts

Collaborative work culture

Qualifications

• Experience building and scaling recommender systems.
• Strong programming skills and software engineering principles.

Responsibilities

• Design and maintain large-scale recommender systems.
• Conduct experiments to inform product decisions.
• Mentor junior team members.

Skills

Deep Learning

Machine Learning

Programming

Collaboration

Tools

Machine Learning Frameworks

Job description

We are seeking a Senior Applied Scientist with expertise in deep learning to join a cross-functional team focused on developing large-scale recommender systems. This role plays a key part in enhancing the user experience by ensuring relevant content and products are surfaced to customers in real time, and at scale.

Youll be joining a team that owns the full lifecycle of the recommendation enginefrom research and prototyping through to production deployment and performance monitoring. This is a hands-on role where you will shape algorithmic direction, mentor peers, and help scale high-impact solutions across a fast-moving digital platform.

Key Responsibilities

• Design, develop, and maintain large-scale recommender systems using advanced machine learning techniques.

• Conduct large-scale experiments to test hypotheses and inform product decisions.

• Deliver production-grade models and pipelines that operate at high traffic volumes.

• Stay current with developments in machine learning research and help integrate state-of-the-art solutions.

• Collaborate with engineers, data scientists, and product teams to define requirements and deploy features.

• Mentor junior team members and support their technical growth.

• Contribute to a culture of continuous learning, inclusion, and innovation across the organization.

Were 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, youre free to be your true self without judgement, and channel your creativity into a platform used by millions.

But how are we showing up? Were 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.

About You

• You have practical experience building and scaling recommender systems or applying deep learning to complex problems in real-world settings.

• Comfortable working in cross-disciplinary teams, collaborating with both technical and non-technical stakeholders.

• Strong programming skills in a modern programming language and experience with common machine learning frameworks.

• A solid grasp of software engineering principles and the full development lifecycle.

• Able to lead by example, offering mentorship and guidance within technical teams.

• You may have contributed to academic or industry publications and are eager to remain engaged with the broader ML research community.

Whats in it for you?

• Competitive compensation package and benefits

• Access to continuous learning and development resources

• Flexible working arrangements and wellbeing support

• Paid annual leave including additional celebration days

• Employee perks, including product discounts and internal events

• A collaborative and inclusive work culture