Senior MLOps Engineer at ASOS

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

31 Dec, 25

Salary

0.0

Posted On

02 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Deep Learning, Distributed Computing, Multi-Instance Clusters, Data Pipelines, CI/CD, Containerisation, Observability, Technical Leadership, Mentoring, Coaching, Causal Algorithms, Batch Processing, Online Models, Software Development Lifecycles, ML Ops

Industry

Retail Apparel and Fashion

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 looking for a Senior Machine Learning Engineer, with expertise in deep learning, to join our growing ML community at ASOS. In role, you will be a senior individual contributor who will be productionising machine learning systems across that help our customers discover and shop complete outfits that resonate with both their personal style and current fashion trends. Our mission is to elevate the fashion experience and ship with high scale ML capabilities. What you’ll be doing: You will be part of an agile, cross-functional team building and improving our causal algorithms for the pricing and customer targeting space. You will be working alongside scientists in driving the implementation and deployment of at-scale solutions for our hundreds of millions of customers/products, creating measurable impact across the business. You will be deploying batch and online machine learning models at high scale. You will be continually developing and improving our code and technology, taking an active role in the conception of brand-new features. You will be mentoring and coaching junior members of the team, supporting their technical progress. You will contribute to the team's technical direction, establish ML standards, and drive quality across ASOS's ML community, while sharing expertise gained from the team. We believe being together in person helps us move faster, connect more deeply, and achieve more as a team. That’s why our approach to working together includes spending at least 2 days a week in the office. It’s a rhythm that speeds up decision-making, helps ASOSers learn from each other more quickly, and builds the kind of culture where people can grow, create, and succeed. Qualifications About You You have professional experience in machine learning with expertise in deep learning methods and their practical applications in production environments. You possess mastery of deep learning frameworks and distributed computing frameworks for implementing large-scale deep learning models. You have proven ability to create and manage multi-instance clusters for distributed and parallel training across GPUs, demonstrating proficiency in data and model parallelism techniques. You have strong understanding of software development lifecycles and engineering practices (Data pipelines, CI/CD, containerisation, observability) - specifically ML Ops principles, techniques and tooling. You’re comfortable providing technical leadership, mentoring, and coaching to more 1-2 junior engineers. You will contribute to wider engineering initiatives across ASOS. Additional Information BeneFITS’ Employee discount (hello ASOS discount!) ASOS Develops (personal development opportunities across the business) Employee sample sales Access to a huge range of LinkedIn learning materials 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

Responsibilities

You will be a senior individual contributor responsible for productionising machine learning systems to enhance customer experience. This includes deploying models at scale and mentoring junior team members.