Machine Learning Engineer

ASOS; Greater London; On-site; GBP 125,000 - GBP 150,000; Full time

Job summary

A leading online fashion retailer in Greater London is seeking a Machine Learning Engineer to join a cross-functional team. The successful candidate will design and implement machine learning models to address varied business challenges, especially in pricing and customer targeting. We offer a competitive salary, a performance-based bonus scheme, and a supportive workplace culture that fosters creativity and inclusion.

Benefits

Competitive salary and performance-based bonus scheme

Generous employee discount

Structured personal and professional development opportunities

Paid annual leave plus an additional day for personal milestones

Flexible benefits allowance

Private medical care options

Qualifications

• Hands-on experience in developing and deploying machine learning solutions.
• Proficiency in training models using GPUs and familiarity with deployment workflows.
• Knowledge of software development practices including version control and monitoring.

Responsibilities

• Collaborate with teams to design and implement machine learning models.
• Deploy and maintain machine learning systems at scale.
• Work with data scientists to translate models into production-ready solutions.

Skills

deep learning

machine learning solutions

modern ML frameworks

distributed computing

CI/CD

communication skills

Job description

We are seeking a Machine Learning Engineer with a strong foundation in deep learning to join a cross-functional team. You'll work closely with data scientists and engineers to deliver impactful machine learning solutions across a wide range of data-rich challenges.

In this role, you'll contribute to developing and deploying advanced algorithms that influence key areas like pricing strategies and personalised customer targeting, all at enterprise scale.

Key Responsibilities

• Collaborate with cross-functional teams to design, implement, and optimize machine learning models for real-world business use cases.
• Deploy and maintain both batch and real-time machine learning systems at scale.
• Work alongside data scientists to translate experimental models into robust production-ready solutions.
• Continuously improve model accuracy, system efficiency, and platform capabilities.
• Contribute to defining team best practices and engineering standards in machine learning development.
• Stay up to date with the latest industry research and bring new insights to the wider ML community within the business.

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

• Hands-on professional experience in developing and deploying machine learning solutions, with a focus on deep learning.
• Experience working with modern ML frameworks and familiarity with end-to-end deployment workflows.
• Proficiency in training models using GPUs, and a strong interest in distributed computing and scalable systems.
• Familiar with software development practices including version control, CI/CD, containerization, and monitoring, especially within ML Ops workflows.
• A collaborative mindset with strong communication skills and the ability to work effectively across multidisciplinary teams.
• Motivated self-starter with a desire to learn, share knowledge, and grow in a fast-paced environment.

BeneFITS

• Competitive salary and performance-based bonus scheme
• Generous employee discount and exclusive product access
• Structured personal and professional development opportunities
• Paid annual leave plus an additional day for special personal milestones
• Flexible benefits allowance and private medical care options
• Access to a variety of online learning resources and employee-led communities
• A supportive, inclusive, and dynamic workplace where innovation thrives