< Back to search
ASOS • London, United Kingdom

Machine Learning Engineer

8.8

/10

Transparency ranking
Apply now

Job Description

Company Description

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.

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.

Qualifications

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.

Additional Information

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

Company benefits

25 days annual leave + bank holidays
401K
Accrued annual leave – Max 5 days to carry over
Adoption leave – 26 weeks enhanced pay
Annual bonus
Annual pay rises
Bike parking
Birthday off
Buy or sell annual leave
Cinema discounts
Coffee discounts
Company freebies
Compassionate leave
Critical Illness Insurance
Dental coverage
Early finish Fridays
Emergency leave
Employee assistance programme
Employee discounts
Enhanced maternity leave – 26 weeks enhanced pay
Enhanced paternity leave – 8 weeks enhanced pay
Enhanced pension match/contribution
Enhanced sick days
Enhanced sick pay
Eye Care Support
Faith rooms
Family health insurance
Fertility benefits
Financial coaching
Further education support
Gym membership
Hackathons
Health insurance
In house training
On-site catering
On-site massages
On-site workout classes
On-site yoga classes
Learning platform
Life assurance
Mental health first aiders
Mental health platform access – Access to EAP (Unum)
Mentoring
Neo-natal leave – 16 weeks leave
On-site gym
On-site wellness room
Open to compressed hours
Open to part time work for some roles
Open to part-time employees
Personal development days
Pregnancy loss leave – 10 days paid leave
Private GP service
Professional subscriptions
Referral bonus
Religious celebration leave
Restaurant discounts
Sabbaticals
Salary sacrifice
Shared parental leave – 26 weeks enhanced pay
Skilled worker visas
Study support
Teambuilding days
Time off in-lieu
Travel loan
Volunteer days
Summer hours

Working at ASOS

Company employees:

3,000

Gender diversity (m:f):

35:65

Hiring in countries

Türkiye

United Kingdom

Office Locations

Other jobs you might like