Engineering Lead - Style Discovery

TN United Kingdom; London; On-site; GBP 80,000 - 110,000; Full time

Job summary

A leading company is seeking an Engineering Lead for their Style Discovery team in London. This role focuses on developing machine learning technologies to enhance customer experiences. The successful candidate will lead a team, oversee software architecture, and ensure high-quality ML solutions for fashion discovery.

Benefits

Employee discount

Personal development opportunities

Employee sample sales

Access to LinkedIn Learning

25 days paid leave

Discretionary bonus scheme

Private medical care

Flexible benefits allowance

Qualifications

• Experience in machine learning with real-world applications.
• Strong understanding of ML Ops principles and tooling.

Responsibilities

• Lead an agile team to design and deliver scalable ML solutions.
• Mentor team members and contribute to technical direction.

Skills

Machine Learning

Deep Learning

Software Development

Mentoring

Tools

PyTorch

TensorFlow

Horovod

DeepSpeed

Job description

Engineering Lead - Style Discovery, London

Client: ASOS

Location: London, United Kingdom

Job Category: -

EU work permit required: Yes

Job Reference: 6c6c4d012c6e

Job Views: 4

Posted: 12.05.2025

Expiry Date: 26.06.2025

Job Description

You’ll be joining our Style Discovery team in our Customer Experience domain. The team will be responsible for developing machine learning technology to enable exciting and unique user experiences. We are mobile-first, science-led, data-driven, and operate under a product model, working closely with product managers and designers to create the best shopping experiences for our customers.

In this role, you will lead a team at the core of applying science to enhance the fashion experience, helping customers discover and shop complete outfits that match their style and current trends.

Engineering Leads are both technical leaders and people managers. They oversee how software is built, covering architecture, design, coding, and quality, while also focusing on team growth, skills development, and performance. Their Product Manager counterparts focus on the 'why' of what is built, aligning with business goals.

What you will be doing

• Working within an agile team of scientists, machine learning engineers, and data engineers to design and deliver scalable ML solutions impacting hundreds of millions of customers and products.
• Supporting our services during high-demand trading periods.
• Collaborating across teams to ensure customer experience remains a priority in organizational initiatives.
• Sharing knowledge and driving engineering improvements through community involvement.
• Developing and enhancing our codebase and technology, including new features.
• Mentoring team members to support their technical growth.
• Contributing to the technical direction, establishing ML standards, and promoting quality across ASOS's ML community.
• Continuously learning and developing skills through Tech Develops days and hackathons.

Qualifications

About You

• Experience in machine learning, with expertise in deep learning and real-world applications.
• Strong understanding of software development lifecycle and engineering practices, especially ML Ops principles and tooling.
• Proficiency with deep learning frameworks (PyTorch, TensorFlow) and distributed computing frameworks (Horovod, DeepSpeed).
• Ability to manage multi-instance clusters for distributed training across GPUs, with skills in data and model parallelism.
• Experience providing technical leadership, mentoring, and coaching to engineers, scientists, and data professionals.

Additional Information

Benefits

• Employee discount (hello ASOS discount!)
• Personal development opportunities via ASOS Develops
• Employee sample sales
• Access to LinkedIn Learning
• 25 days paid leave + a celebration day
• Discretionary bonus scheme
• Private medical care
• Flexible benefits allowance

Check #InsideASOS on social media to see what life at ASOS is like. Discover our tech-powered approach via the ASOS Tech Podcast and Tech Blog links provided.