Senior Machine Learning Scientist - Search (London)

Job Description

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.

• 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.)

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).

• 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.