Staff Machine Learning Scientist
Depop
Staff Machine Learning Scientist
Depop
Peer-to-peer fashion marketplace with commissions
Company Description
Depop is a peer-to-peer circular fashion marketplace where anyone can buy, sell and discover secondhand fashion. Our mission is simple: to make fashion circular by making secondhand as exciting and rewarding as buying new.
Founded in 2011, Depop’s diverse community has helped move resale into the mainstream, where buying secondhand is no longer an alternative, but how people of different ages now engage with fashion. Today, more than 56 million registered users come to Depop to find great value, express their own personal style and give clothes a longer life. We believe that everything you want already exists, and our role is to help people discover it.
Powered by a team of over 500 people, our company is headquartered in London, with offices in New York. In 2021, Depop became a wholly-owned subsidiary of Etsy - the global marketplace for unique and creative goods - and continues to operate as a standalone company. For more information, visit www.depop.com
We aim 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.
AI Disclosure: We use AI tools (Google Gemini) to help our team source and review applications for roles with a high volume of applications. These tools assist our recruiters in identifying great talent but do not replace human decision-making. At Depop, every hiring decision is made by a human.
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 [email protected].
Depop is looking for a talented Staff ML Scientist to join our Ranking ML team in the UK. You will work alongside a cross-functional team of Product Managers, ML Engineers, and fellow ML Scientists, helping build and maintain ranking models to power Depop's app, serving millions of personalised results to users daily.
As a staff-level member of the team, you will be expected to set the technical vision, lead high-impact initiatives, and mentor and coach others to drive innovation at scale, while working across multiple domains and stakeholders.
You will:
Lead the design and deployment of advanced ranking models for Depop’s entire app, covering personalised recommendations, search results and other surfaces.
Collaborate closely with cross-functional partners (product, engineering, data) to define problems, translate them into scalable solutions, and deliver measurable business outcomes.
Lead the end-to-end lifecycle of ML projects: from ideation, data acquisition, feature engineering, training, and evaluation to deployment and ongoing iteration.
Drive innovation in ranking by researching and integrating emerging ML techniques, frameworks, and tooling, while contributing technical expertise to long-term product and data strategy.
Mentor, coach, and set technical direction within the Ranking ML team, helping others grow and innovate.
Act as a thought leader in the ranking space, sharing learnings internally, engaging with the wider ML community, and showcasing our work externally.
Skills and Experience
Significant experience working as a Machine Learning Scientist, with a proven track record of delivering and scaling models that solve complex, real-world problems with measurable business impact
Proven track record in designing and optimizing learning-to-rank models
Deep understanding of machine learning concepts and frameworks
Proven ability to productionize ML models and pipelines: from prototyping to deployment, with strong experience in monitoring, iteration, and troubleshooting.
Advanced programming skills in Python and familiarity with ML frameworks such as PyTorch, TensorFlow, or similar.
Experience leading projects and mentoring engineers or scientists, with a track record of fostering team growth and technical excellence.
Excellent communication skills: able to bridge technical and non-technical stakeholders and influence decision making.
Committed to responsible AI practices, including attention to ethics, fairness, and inclusivity.
A genuine curiosity about AI and a willingness to explore how it can enhance your day-to-day work
Additional Information
Health + Mental Wellbeing
Work/Life Balance:
Family Life:
Learn + Grow:
Your Future:
Depop Extras:
Depop is a peer-to-peer online marketplace for fashion where users buy, sell, and discover unique items such as vintage pieces, streetwear, sneakers, and designer pieces. Items are listed by users who set prices and descriptions; buyers purchase through the platform, and Depop earns revenue by taking a commission on each sale. The product works through user-generated listings, a social-feel interface with following and messaging, and a payments process that handles transactions. Depop differentiates itself from competitors by targeting a young, fashion-forward audience with a strong emphasis on sustainability, second-hand items, and community engagement, along with a marketplace that blends social discovery with shopping for both well-known brands and independent designers. Its goal is to grow a global, diverse fashion ecosystem where people can easily buy and sell unique, sustainable clothing items while connecting with others who share interest in fashion.
Explore more opportunities at Depop