Senior Machine Learning Engineer (Personalisation)

asos.com Ltd; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

25 days annual leave

Discretionary bonus

Private medical care

Flexible benefits

Personalised learning

Sample sales

Job summary

ASOS is seeking a Senior Machine Learning Engineer to join the Search & Recommendations group. You will design and operate large-scale ML systems powering product discovery, recommendations and personalization for millions of customers.

You’ll collaborate with scientists, engineers and product managers to deploy impactful solutions at scale. You will lead ML initiatives, contribute to the technical roadmap, and mentor other engineers while advancing production-grade ML capabilities in a

Qualifications

• Experience applying ML and DL techniques in production.
• Familiarity with distributed training and GPU-based environments.
• Strong software engineering and MLOps practices.

Responsibilities

• Design, build and operate production ML systems at scale.
• Collaborate with scientists, engineers and PMs to deploy solutions.
• Develop and deploy batch and real-time ML models in production.
• Improve recommendation, ranking and personalization capabilities.
• Contribute to ML standards and best practices across teams.
• Mentor engineers through coaching and knowledge sharing.
• Help shape technical direction of the ML community.

Skills

ML in production

Deep learning

Distributed computing

MLOps

Technical leadership

Cross-functional collaboration

Tools

TensorFlow

PyTorch

Spark

Job description

• Full-time

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'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.

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.

Qualifications

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.
• 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.

Additional Information

• 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