At a Glance
- Tasks: Join a dynamic team to build and enhance machine learning systems for fashion discovery.
- Company: ASOS, a leading fashion retailer with a focus on innovation.
- Benefits: Enjoy employee discounts, flexible benefits, and 25 days of annual leave.
- Other info: Mentorship opportunities and a chance to shape the future of fashion tech.
- Why this job: Make a real impact in the fashion industry using cutting-edge machine learning technology.
- Qualifications: Expertise in deep learning and experience in production environments required.
The predicted salary is between 70000 - 90000 £ per year.
We are looking for a Senior Machine Learning Engineer, with expertise in deep learning, to join our cross-functional Outfits Discovery team. In this role you will be a senior IC who will be productionising machine learning systems 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.
Responsibilities
- 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.
Qualifications
- 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.
Benefits
- Employee discount (hello ASOS discount!)
- 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
Machine Learning Engineer (Recommendations) employer: We're Asos
ASOS is an exceptional employer that fosters a dynamic and innovative work culture, particularly for Machine Learning Engineers. With a strong emphasis on employee growth, you will have the opportunity to mentor junior team members while working on cutting-edge technology that shapes the future of fashion. Located in a vibrant environment, ASOS offers generous benefits including employee discounts, flexible allowances, and a commitment to personal development, making it a rewarding place to advance your career.
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We think this is how you could land Machine Learning Engineer (Recommendations)
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We think you need these skills to ace Machine Learning Engineer (Recommendations)
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
