Read on to find out what you will need to succeed in this position, including skills, qualifications, and experience. Depop is looking for a versatile Senior Machine Learning Scientist to join our Search & Ranking 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: Research, design, and deliver ML solutions to address problems within the search & discovery space, such as: Learning-to-rank models Vector search & embedding models etc.

Understand requirements from various partners across the business, designing machine learning solutions to solve business problems, such as: How can we surface relevant results for this search? How can we show users personalized 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 Skills and experience Significant experience (3+ years) working as a Data Scientist, with a track record of delivering models to solve industry-scale problems. 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 the ability to work with multi-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 other cloud platforms (GCP/Azure). Additional Information Health & Mental Wellbeing: PMI and cash plan healthcare, subsidized counseling, cycle to work scheme, Employee Assistance Program, Mental Health First Aiders. Work/Life Balance: 25 days annual leave, impact hours, paid volunteering leave, sabbatical after 5 years. Flexible Working: hybrid model with options for Flex, Office Based, and Remote (role-dependent), dog-friendly offices, work abroad options. Family Life: Paid parental leave, IVF leave, shared parental leave, emergency parent/carer leave. Learn + Grow: budgets for conferences and learning, mentorship programs. Your Future: Life Insurance, pension matching. Depop Extras: Free shipping on UK sales, milestones celebrations.

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