Machine Learning Engineer
Hybrid
London, United Kingdom
Full Time
07-03-2025
Job Specifications
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 Machine Learning Engineer, with expertise in deep learning, to join our cross-functional AI Trade Optimization team.
You will work alongside data engineers and scientists to solve problems and productionise interesting solutions that leverage cutting edge tech. At ASOS, as an online only retailer, we have unique datasets like transactions and click streams for millions of customers and hundreds of thousands of products.
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 contribute to the team's technical direction, contribute to ML standards, and drive quality across ASOS's ML community, while sharing expertise gained from the team.
Qualifications
About You
You have professional experience in machine learning with experience in deep learning methods and their practical applications in production environments.
You have working knowledge of ML frameworks (e.g., PyTorch, TensorFlow) and experience with model deployment.
You have experience with GPU-based model training, with interest in learning advanced distributed computing techniques and parallelization strategies.
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 are a self-starter with a strong desire to learn and grow professionally.
You have excellent communication skills and enjoy collaborating with diverse teams.
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
Why take our word for it? Search #InsideASOS on our socials to see what life at ASOS is like.
Want to find out how we’re tech powered? Check out the ASOS Tech Podcast here https://open.spotify.com/show/6rT4V6N9C7pAXcX60kzzxo. Prefer reading? Check out our ASOS Tech Blog here https://medium.com/asos-techblog.
About the Company
We exist to give people 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 judgment, and channel your creativity into a platform used by millions. Whatever your role, ASOS will encourage you to be you, fulfilling your creative potential with our global reach. Push boundaries, and challenge expectations. We’re determined to succeed, so we’ll trust you to deliver. Help drive our journey to becoming the global fashion destination for 20-somethings... Know more
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