Staff Machine Learning Scientist - Core ML

Depop • Full-time • London, GB • 14h ago

Company Description

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. Find out more at www.depop.com

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 to adjustments@depop.com. For any other non-disability related questions, please reach out to our Talent Partners.

Role

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.

Responsibilities

You will:

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 whiteboarding sessions, and planning/roadmapping, 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

Qualifications

Skills and Experience

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

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, to give you a chance to recharge or do something you love.
Flexible Working: MyMode hybrid-working model with Flex, Office Based, and Remote options *role dependant
All offices are dog-friendly
Ability to work abroad for 4 weeks per year in UK tax treaty countries

Family Life