Overview

Depop is looking for a dedicated Machine Learning Scientist to join our new Core 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 foundational machine learning models and infrastructure, such as product matching models, image embedding services, and lightweight classifiers, that support multiple product and marketing use cases across Depop.

Responsibilities

• Research, design and deliver machine learning solutions to solve cross-cutting problems within the fashion resale space
• Work with and finetune models for representation learning, computer vision, and classification
• Understand requirements from various stakeholders across the business, designing general-purpose machine learning solutions to power features like content understanding, moderation, and personalization
• Set up and conduct large-scale experiments to test hypotheses and drive model and product improvements
• Keep up to date with research, contribute to internal knowledge sharing and ML best practices, and help the team stay informed about new techniques and approaches relevant to our work
• Participate in team ceremonies, such as agile cadences, technical whiteboarding sessions, and planning/roadmapping
• Report and present technical findings to technical and non-technical audiences

Qualifications

• Experience working as a Machine Learning Scientist, with a track record of delivering models to solve industry-scale problems
• Solid understanding of machine learning concepts, familiarity with frameworks such as Transformers, PyTorch or TensorFlow
• Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps
• 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 NLP, image classifiers, deep learning, or large language models
• Experience with experiment design and conducting A/B tests
• Experience building shared or platform-style ML systems
• Experience with Databricks and PySpark
• Experience working with AWS or another cloud platform (GCP/Azure)

Additional information

• Health + Mental Wellbeing: PMI and cash plan healthcare access with Bupa; subsidised counselling and coaching with Self Space
• Cycle to Work scheme with options from Evans or the Green Commute Initiative
• Employee Assistance Programme (EAP) for 24/7 confidential support; Mental Health First Aiders across the business for support and signposting
• Work/Life Balance: 25 days annual leave with option to carry over up to 5 days; 1 company-wide day off per quarter; Impact hours: Up to 2 days additional paid leave per year for volunteering
• Fully paid 4 week sabbatical after completion of 5 years of consecutive service with Depop
• Flexible Working: MyMode hybrid-working model with Flex, Office Based, and Remote options (role dependent)
• All offices are dog-friendly; ability to work abroad for 4 weeks per year in UK tax treaty countries
• Family Life: 18 weeks of paid parental leave for full-time regular employees; IVF leave, shared parental leave, and paid emergency parent/carer leave
• Learn + Grow: Budgets for conferences, learning subscriptions, and more; Mentorship and programmes to upskill employees
• Your Future: Life Insurance (3x salary) and Pension matching up to 6% of qualifying earnings
• Depop Extras: Employees enjoy free shipping on their Depop sales within the UK; special milestones are celebrated with gifts and rewards