Staff Machine Learning Scientist - Core ML

Depop is the community-powered circular fashion marketplace where anyone can buy, sell and discover desirable secondhand fashion. With a community of over 35 million users, Depop is on a mission to make fashion circular, redefining fashion consumption. Founded in 2011, the company is headquartered in London, with offices in New York and Manchester, and in 2021 became a wholly-owned subsidiary of Etsy. Our mission is to make fashion circular and to create an inclusive environment where everyone is welcome, no matter who they are or where they’re from. Just as our platform connects people globally, we believe our workplace should reflect the diversity of the communities we serve. We thrive on the power of different perspectives and experiences, knowing they drive innovation and bring us closer to our users.

We’re proud to be an equal opportunity employer, providing employment opportunities without regard to age, ethnicity, religion or belief, gender identity, sex, sexual orientation, disability, pregnancy or maternity, marriage and civil partnership, or any other protected status. We’re continuously evolving our recruitment processes to ensure fairness and are open to accommodating any needs you might have. If, due to a disability, you need adjustments to complete the application, please let us know by sending an email with your name, the role to which you would like to apply, and the type of support you need to complete the application.

Depop is looking for a Staff Machine Learning Scientist to join our new Core ML team in the UK. You will work alongside a multi-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 staff-level member of the team, you will be expected to set the technical vision, lead high-impact initiatives, and coach others to drive innovation at scale, while working across multiple domains and partners.

• Own the design, development, and deployment of 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 own efforts to productionize, scale, and evolve them as shared systems.
• Partner closely with senior stakeholders across the business to define problems, and lead the design of general-purpose, scalable ML solutions that power features like content understanding, moderation, and personalisation.
• Lead the end-to-end lifecycle of large-scale experiments, from hypothesis generation through evaluation, to guide model and product improvements, ensuring statistical difficulty and real-world applicability.
• Stay up to date with research, actively contribute to internal knowledge sharing and ML best practices, and chip in technical expertise to long-term product and data strategy.
• Participate in team ceremonies, such as agile cadences, technical white-boarding sessions, and planning/road-mapping, setting technical direction and improving for the team.
• Communicate technical findings clearly and confidently to both technical and non-technical audiences, including senior stakeholders, and influence decision making.

• Proven track record of delivering and scaling models that solve complex, real-world problems with measurable business impact.
• 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 the end-to-end lifecycle of ML initiatives, work independently in ambiguous problem spaces, and mentor and grow other scientists and engineers.
• Strong collaboration and interpersonal skills, with experience aligning technical approaches with multi-functional teams and stakeholders.

• 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).

• Health + Mental Wellbeing: PMI and cash plan healthcare access; Sub-sidised counselling and coaching; Cycle to Work scheme; 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; Up to 2 days additional paid leave per year for volunteering; Fully paid 4-week sabbatical after completion of 5 years of consecutive service.
• Flexible Working: MyMode hybrid-working model with Flex, Office-Based, and Remote options—all 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 up-skill employees.
• Your Future: Life Insurance (financial compensation of 3x your salary); 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!