Staff Machine Learning Scientist, Ranking

Company Description

Depop is a peer-to-peer circular fashion marketplace where anyone can buy, sell and discover secondhand fashion. Our mission is simple: to make fashion circular by making secondhand as exciting and rewarding as buying new.

Founded in 2011, Depop’s diverse community has helped move resale into the mainstream, where buying secondhand is no longer an alternative, but how people of different ages now engage with fashion. Today, more than 56 million registered users come to Depop to find great value, express their own personal style and give clothes a longer life. We believe that everything you want already exists, and our role is to help people discover it.

Powered by a team of over 500 people, our company is headquartered in London, with offices in New York. In 2021, Depop became a wholly-owned subsidiary of Etsy - the global marketplace for unique and creative goods - and continues to operate as a standalone company. For more information, visit www.depop.com

We aim 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.

AI Disclosure: We use AI tools (Google Gemini) to help our team source and review applications for roles with a high volume of applications. These tools assist our recruiters in identifying great talent but do not replace human decision-making. At Depop, every hiring decision is made by a human.

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 [email protected].

Role

Depop is looking for a talented Staff ML Scientist to join our Ranking 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 ranking models to power Depop's app, serving millions of personalised results to users daily.

As a staff-level member of the team, you will be expected to set the technical vision, lead high-impact initiatives, and mentor and coach others to drive innovation at scale, while working across multiple domains and stakeholders.

Responsibilities

You will:

• Lead the design and deployment of advanced ranking models for Depop’s entire app, covering personalised recommendations, search results and other surfaces.

• Collaborate closely with cross-functional partners (product, engineering, data) to define problems, translate them into scalable solutions, and deliver measurable business outcomes.

• Lead the end-to-end lifecycle of ML projects: from ideation, data acquisition, feature engineering, training, and evaluation to deployment and ongoing iteration.

• Drive innovation in ranking by researching and integrating emerging ML techniques, frameworks, and tooling, while contributing technical expertise to long-term product and data strategy.

• Mentor, coach, and set technical direction within the Ranking ML team, helping others grow and innovate.

• Act as a thought leader in the ranking space, sharing learnings internally, engaging with the wider ML community, and showcasing our work externally.

Qualifications

Skills and Experience

• Significant experience working as a Machine Learning Scientist, with a proven track record of delivering and scaling models that solve complex, real-world problems with measurable business impact

• Proven track record in designing and optimizing learning-to-rank models

• Deep understanding of machine learning concepts and frameworks

• Proven ability to productionize ML models and pipelines: from prototyping to deployment, with strong experience in monitoring, iteration, and troubleshooting.

• Advanced programming skills in Python and familiarity with ML frameworks such as PyTorch, TensorFlow, or similar.

• Experience leading projects and mentoring engineers or scientists, with a track record of fostering team growth and technical excellence.

• Excellent communication skills: able to bridge technical and non-technical stakeholders and influence decision making.

• Committed to responsible AI practices, including attention to ethics, fairness, and inclusivity.

• A genuine curiosity about AI and a willingness to explore how it can enhance your day-to-day work

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 of annual leave with the option to carry over up to 5 days
• Impact hours: Up to 2 days of 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-dependent
• All offices are dog-friendly

Family Life:

• For birth parent: 20 weeks of paid parental leave for full-time regular employees
• For non-birth parents: 12 weeks of paid parental leave for full-time regular employees
• IVF leave, shared parental leave, and paid emergency parent/carer leave

Learn + Grow:

• Twice-yearly development chats and yearly performance reviews
• Learning budget
• Upskilling our employees with company-wide training workshops, materials and resources

Your Future:

• Life Insurance (financial compensation of 3x your salary)
• Pension matching up to 6% of full base salary with Aviva

Depop Extras:

• In-office Depop Shop (that’s free!) and a packing station with free delivery.
• Special milestones are celebrated with gifts and rewards!