Machine Learning Scientist

Depop • Full-time • London, GB • 1w ago

Company Description

Depop is the community-powered circular fashion marketplace where anyone can buy, sell and discover desirable secondhand fashion. With a community of over 35 million users, Depop is on a mission to make fashion circular, redefining fashion consumption. Founded in 2011, the company is headquartered in London, with offices in New York and Manchester, and in 2021 became a wholly-owned subsidiary of Etsy. Find out more at www.depop.com

Our mission is to make fashion circular and to create an inclusive environment where everyone is welcome, no matter who they are or where they’re from. Just as our platform connects people globally, we believe our workplace should reflect the diversity of the communities we serve. We thrive on the power of different perspectives and experiences, knowing they drive innovation and bring us closer to our users. We’re proud to be an equal opportunity employer, providing employment opportunities without regard to age, ethnicity, religion or belief, gender identity, sex, sexual orientation, disability, pregnancy or maternity, marriage and civil partnership, or any other protected status. We’re continuously evolving our recruitment processes to ensure fairness and are open to accommodating any needs you might have.

If, due to a disability, you need adjustments to complete the application, please let us know by sending an email with your name, the role to which you would like to apply, and the type of support you need to complete the application to adjustments@depop.com. For any other non-disability related questions, please reach out to our Talent Partners.

The Role

Depop is looking for a dedicated Machine Learning Scientist to join our Listings & Inventory team in the UK. You will work alongside a cross functional team of Product Managers, Designers, Backend & Frontend Engineers and other Data Scientists playing a key role in building innovative machine learning models to power Depop’s selling experience.

Responsibilities

Research, design and deliver machine learning solutions to solve problems within the fashion resale space:
Working with and fine tuning (multimodal) large language models; Textual understanding using natural language processing algorithms / Image feature extraction using computer vision models
Understand requirements from various stakeholders across the business, designing machine learning solutions to solve business problems, such as: How can we capitalise on recent advances in generative AI to make the selling process as easy as possible and how can we extract information from image and text inputs to generate rich features used in our recommender and search engines?
Set up and conduct large-scale experiments to test hypotheses and drive product development
Keep up to date with research, contribute to Machine Learning groups, and apply new techniques for (multimodal) LLMs, NLP, computer vision, etc.
Participate in team ceremonies (follow the agile cadence, technical whiteboarding sessions, product road mapping, etc)
Report and present technical findings to technical and non-technical audiences

Requirements

Experience working as a Machine Learning Scientist, with a track record of delivering models to solve industry-scale problems
Solid understanding of machine learning concepts, familiarity working with frameworks such as Transformers, PyTorch or TensorFlow
Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps
Collaborative and humble team player with an ability to work with cross-functional teams, including technical and non-technical stakeholders
Passion for learning new skills and staying up-to-date with ML algorithms

Bonus

Experience working with NLP, Image classifiers and Transformers
Experience with deep learning & large language models
Experience with experiment design and conducting A/B tests
Experience with Databricks and PySpark
Experience working with AWS or another cloud platform (GCP/Azure)

Additional Information

Health + Mental Wellbeing

PMI and cash plan healthcare access with Bupa
Subsidised counselling and coaching with Self Space
Cycle to Work scheme with options from Evans or the Green Commute Initiative
Employee Assistance Programme (EAP) for 24/7 confidential support
Mental Health First Aiders across the business for support and signposting

Work/Life Balance

25 days annual leave with option to carry over up to 5 days
1 company-wide day off per quarter
Impact hours: Up to 2 days additional paid leave per year for volunteering
Fully paid 4 week sabbatical after completion of 5 years of consecutive service with Depop, to give you a chance to recharge or do something you love.
Flexible Working: MyMode hybrid-working model with Flex, Office Based, and Remote options *role dependant
All offices are dog-friendly
Ability to work abroad for 4 weeks per year in UK tax treaty countries

Family Life