Senior Machine Learning Scientist - Recommendations
Team: Engineering & Data
Location: Depop - London
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 . For any other non-disability related questions, please reach out to our Talent Partners.
Life is about creating. That's why we're home to over 30 million artists, stylists, designers, sneakerheads — and you? We're the community-powered, circular-minded marketplace changing the world of online fashion. Now it's time to get inspired at Depop.
Responsibilities
Job description
Job Description
Depop is looking for a versatile Senior Machine Learning Scientist to join our Recommendations team in the UK. As part of the team you will work alongside a Product Manager, Backend Engineers and other ML Scientists playing a key role in building innovative models to power Depop’s search engine and ranking across the app.
Responsibilities:
You will:
Research, design and deliver ML solutions to take on problems within the search & discovery space:
Learning-to-rank models
Vector search & embedding models
etc.
Understand requirements from various partners across the business, designing machine learning solutions to address business problems, such as:
How can we surface relevant results for this search?
How can we show users personalised results in real time?
What is the right price for this user?
Set up and conduct large-scale experiments to test hypotheses and drive product development
Keep up to date with pioneering research, contribute to Machine Learning groups, and apply new techniques for NLP, image processing, etc.
Participate in team ceremonies (follow the agile cadence, technical whiteboarding sessions, product road mapping, etc)
Qualifications
Significant experience (3+ years) working as a Machine Learning Scientist, with a track record of delivering models to solve industry-scale problem
Experience with experiment design and conducting A/B tests
Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps
Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch
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 points
Experience with Databricks and PySpark
Experience with deep learning & large language models
Experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch)
Experience working with AWS or another cloud platform (GCP/Azure)
