Senior Machine Learning Scientist (Basé à London)

Role

Depop is looking for a Senior 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.

As a senior member of the team, you will be expected to take ownership of high-impact projects, lead technical direction on core modelling efforts, and mentor others while working across multiple domains and stakeholders.

Responsibilities

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• Research, design, and deliver robust machine learning solutions to solve cross-cutting problems within the fashion resale space.
  
• Work with and fine-tune models for representation learning, computer vision, and classification, and lead efforts to productionise and scale them.
  
• Identify and define requirements from multiple stakeholders across the business, and lead the design of general-purpose machine learning solutions that power features like content understanding, moderation, and personalization.
  
• Set up and conduct large-scale experiments to test hypotheses and guide model and product improvements, ensuring statistical rigour and real-world applicability.
  
• Stay up to date with research, actively contribute to internal knowledge sharing and ML best practices, and help shape the long-term technical strategy for the team.
  
• Participate in team ceremonies, such as agile cadences, technical whiteboarding sessions, and planning/roadmapping.
  
• Communicate technical findings clearly and confidently to both technical and non-technical audiences, including senior stakeholders.
  

Qualifications
Skills and Experience:

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• Significant experience working as a Machine Learning Scientist, with a proven track record of delivering and scaling models that solve complex, real-world problems.
  
• Deep understanding of machine learning concepts and experience applying them in production settings, using frameworks such as Transformers, PyTorch, or TensorFlow.
  
• Strong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles.
  
• Ability to lead end-to-end ML projects, work independently in ambiguous problem spaces, and mentor junior team members.
  
• Strong collaboration and communication skills, with experience aligning technical approaches with cross-functional teams and stakeholders.
  

Bonus Points

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• 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).
  

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