Depop

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 <a href="http://www.depop.com" rel="nofollow noopener" target="_blank">www.depop.com</a> 
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 <a href="mailto:adjustments@depop.com" rel="nofollow noopener" target="_blank">adjustments@depop.com</a>.
<h1>Role</h1>
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.
<h2>Responsibilities</h2>
You will:
<ul>
<li>Own the design, development, and deployment of robust machine learning solutions to solve cross-cutting problems within the fashion resale space</li>
<li>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</li>
<li>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</li>
<li>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</li>
<li>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</li>
<li>Participate in team ceremonies, such as agile cadences, technical whiteboarding sessions, and planning/roadmapping, setting technical direction and improving for the team</li>
<li>Communicate technical findings clearly and confidently to both technical and non-technical audiences, including senior stakeholders, and influence decision making</li>
</ul>
<h2>Qualifications</h2>
Skills and Experience
<ul>
<li>Proven track record of delivering and scaling models that solve complex, real-world problems with measurable business impact</li>
<li>Deep understanding of machine learning concepts and experience applying them in production settings, using frameworks such as Transformers, PyTorch, or TensorFlow</li>
<li>Strong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles</li>
<li>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</li>
<li>Strong collaboration and interpersonal skills, with experience aligning technical approaches with multi-functional teams and stakeholders</li>
</ul>
Bonus Points
<ul>
<li>Experience with NLP, image classifiers, deep learning, or large language models</li>
<li>Experience with experiment design and conducting A/B tests</li>
<li>Experience building shared or platform-style ML systems</li>
<li>Experience with Databricks and PySpark</li>
<li>Experience working with AWS or another cloud platform (GCP/Azure)</li>
</ul>
Additional Information
Health + Mental Wellbeing
<ul>
<li>PMI and cash plan healthcare access with Bupa</li>
<li>Subsidised counselling and coaching with Self Space</li>
<li>Cycle to Work scheme with options from Evans or the Green Commute Initiative</li>
<li>Employee Assistance Programme (EAP) for 24/7 confidential support</li>
<li>Mental Health First Aiders across the business for support and signposting</li>
</ul>
Work/Life Balance:
<ul>
<li>25 days of annual leave with the option to carry over up to 5 days</li>
<li>Impact hours: Up to 2 days of additional paid leave per year for volunteering</li>
<li>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.</li>
<li>Flexible Working: MyMode hybrid-working model with Flex, Office-Based, and Remote options *role-dependent</li>
<li>All offices are dog-friendly</li>
</ul>
Family Life:
<ul>
<li>For birth parent: 20 weeks of paid parental leave for full-time regular employees</li>
<li>For non-birth parents: 12 weeks of paid parental leave for full-time regular employees</li>
<li>IVF leave, shared parental leave, and paid emergency parent/carer leave</li>
</ul>
Learn + Grow:
<ul>
<li>Twice-yearly development chats and yearly performance reviews</li>
<li>Learning budget</li>
<li>Upskilling our employees with company-wide training workshops, materials and resources</li>
</ul>
Your Future:
<ul>
<li>Life Insurance (financial compensation of 3x your salary)</li>
<li>Pension matching up to 6% of full base salary with Aviva</li>
</ul>
Depop Extras:
<ul>
<li>In-office Depop Shop (that’s free!) and a packing station with free delivery.</li>
<li>Special milestones are celebrated with gifts and rewards!</li>
</ul>

Staff Machine Learning Scientist - Core ML

Staff Machine Learning Scientist - Core ML

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