Machine Learning Engineer | Catalogue

London, England, United Kingdom

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Lyst

Shop and discover the world’s most stylish brands, curated for you. With more than 17,000 brands and stores in one place, Lyst is the definitive fashion destination.

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Lyst offers a unique opportunity to work on a premium shopping platform, which is both a trusted partner to the world’s leading fashion brands and a global consumer-facing product. Over 200 million people use the Lyst app and website each year to shop an assortment of 8 million items via a highly personalised experience. Lyst is a scale-up environment, combining an agile mentality with a proven business model and over a decade of experience. This provides a balance between foundations and structure, and autonomy and pace. Our goal is to be the category leading destination for every fashion shopper.

Data and technology sit at the heart of everything we do, and we firmly believe that we can only meet our goals by prioritising our team and culture. We give our people the freedom to drive impact and shape the future of our company, within a diverse, inclusive and high-trust environment. We don’t rely on prescriptive rules, policies and procedures to drive results. We trust the judgement and ownership of our team, and prioritise learning and career development, knowing that our success is only possible thanks to our people. Lyst was founded in London in 2010, and has raised over $160m from leading investors including Accel, Balderton, Molten Ventures, Fidelity International, and LVMH.

We’re looking for a Machine Learning Engineer to come and join our team, to help us build upon and improve our systems that help connect our customers who love fashion with the world’s top fashion brands.

About the team:

You'll join the Catalogue Tribe, a cross-functional department of engineers, data scientists, data analysts, product managers, and fashion experts. The Catalogue Tribe builds, maintains, deduplicates, and enriches the world's largest fashion catalogue of 8M+ in-stock products, enabling a seamless shopping experience and deep personalisation for our customers. As Lyst is inventory-free, the Catalogue Tribe's work is foundational to all of Lyst's business operations, including retailer onboarding and the customer experience.

If you are interested in solving some of the most interesting data problems in the fashion industry, then we would love to hear from you!

  • We maintain about half a dozen services
  • We care about collecting metrics and properly monitoring our services.
  • We work in Python3.
  • We use Kubernetes for managing our services in production.
  • We use CircleCI for continuous integration and moved a lot of our services to be continuously deployed too, which is exciting!
  • We work closely with other teams across tribes, and almost all of Lyst engineering uses our services.
  • We have 2 week sprints, use JIRA and Slack, and hold daily standups.
  • We have innovation time for experimental ideas & actively invest in continuous maintenance.

As a Machine Learning Engineer at Lyst, you’ll be working on one of the teams responsible for making connections between products and our customers, happen. You'll be working on problems involving automated categorisation of products, color detection, deduplication, and size harmonisation, data taxonomisation, and many other interesting enrichment problems.

We solve some unique problems at Lyst, with the largest data catalog of fashion products, you’ll be learning the best solutions as you go. We aim to build software that’s easy to maintain and low on surprises, which is a goal in many of the design approaches we’ve taken.

You’ll have the opportunity for impact by helping teach other engineers new techniques and applications, while collaborating with product managers to help find new ways to apply data science and machine learning in our solutions.

We have a data science chapter, where we hold regular literature reviews and data science training sessions to help spread knowledge of the best techniques available that fit our problem.

Requirements


  • Experience with the creation and maintenance of ML pipelines
  • Comfortable with large datasets
  • Contribute to an inclusive and positive working environment for everyone
  • Being able to communicate clearly and be humble when sharing ideas with everyone on the team
  • Capable of writing production code and doing iterative development, balancing speed to ship and long term maintainability
  • Have a detail oriented mindset and actively demonstrates curiosity

We make great use of both the Python and AWS data science ecosystems to power our solutions. Familiarity with Jupyter, Pandas, PySpark, Sagemaker, Tensorflow and related tools would be helpful.

If you’ve programmed in a different language and not done Python before, that’s OK, knowing how to code is a transferable skill. Equally if you’ve never used AWS before and have experience of an alternative cloud provider, that’s OK too. There’s time to learn on the job and a supportive, knowledgeable team will help you.

We believe in having a curious mindset and your ability to learn to do the job, rather than a checklist of must haves.

Benefits

  • Flexible Working: Our flexible working approach offers a high degree of freedom and autonomy. Individuals are provided with the discretion to work remotely on a regular basis, with an expectation that a reasonable proportion of time is spent in the office to enhance in-person collaboration. If due to unique circumstances this doesn’t quite work, we are open to listening to what will.
  • Time Off: In addition to the 8 statutory bank holidays, you will receive 29 holidays per year. Lyst’s holiday year runs from 1 April to 31 March.
  • Competitive Family Leave Package: This includes Enhanced Family Leave for those eligible, paid Time off for Dependents and Support for Fertility Treatment & Loss.
  • Clothing Benefit: We want you to enjoy using the Lyst app and site as much as our customers, so we provide you with a clothing allowance to use on Lyst every year. This starts at £250 when you join and increases up to £1,000 with your length of service.
  • Private Healthcare: Our healthcare provider is Vitality. Your health is important to us which is why we offer all employees a comprehensive healthcare scheme from the day you start.
  • Training Allowance: We’re big on continuous learning and growth, so all employees are currently entitled to an annual training allowance of £1,000. This can be used to attend conferences, industry events, training courses and to purchase resources.
  • Pension Scheme: Our pension provider is The People’s Pension. We offer a minimum employee contribution of 5% and 3% employer contribution.
  • Eye Tests and Vouchers: Employees can make a saving on their eye test and glasses through our chosen provider. You’ll receive a free eye test every year and a discount towards glasses.
  • Cycle-to-Work Scheme: Lyst will purchase a bicycle from your chosen retailer, you will then receive a voucher to pick up your bicycle from them.
  • Transport Season Ticket Loan: Employees can apply for an interest free season ticket loan to support your travel to work.
  • Social Events: Frequent company wide social events including Christmas & summer parties, sports days, themed drinks, quizzes, cook alongs, as well as smaller team socials. We also have plenty of interest based groups such as football, running club, book club, culinary and more.

Diversity and inclusion is an integral part of our culture. We recognise and celebrate the value and impact diversity brings to our company and are committed to ensuring this is a consistent focus, for which we are held to account. We are committed to treating all applicants fairly and equally, and encourage candidates from all backgrounds to apply for this role.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Agile AWS Engineering Jira Jupyter Kubernetes Machine Learning Pandas Pipelines PySpark Python SageMaker TensorFlow

Perks/benefits: Career development Conferences Fertility benefits Flex hours Flex vacation Health care Startup environment Team events

Region: Europe
Country: United Kingdom
Job stats:  30  9  0

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