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.
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.