Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Scientist

Depop
London
4 weeks ago
Create job alert
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 . For any other non-disability related questions, please reach out to our Talent Partners.

Role

Depop is looking for a dedicated 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.

Responsibilities
  • Research, design and deliver machine learning solutions to solve cross-cutting problems within the fashion resale space
  • Work with and finetune models for representation learning, computer vision, and classification
  • Understand requirements from various stakeholders across the business, designing general-purpose machine learning solutions to power features like content understanding, moderation, and personalization
  • Set up and conduct large-scale experiments to test hypotheses and drive model and product improvements
  • Keep up to date with research, contribute to internal knowledge sharing and ML best practices, and help the team stay informed about new techniques and approaches relevant to our work
  • Participate in team ceremonies, such as agile cadences, technical whiteboarding sessions, and planning/roadmapping
  • Report and present technical findings to technical and non-technical audiences
Qualifications

Skills and Experience

  • Experience working as a Machine Learning Scientist, with a track record of delivering models to solve industry-scale problems
  • Solid understanding of machine learning concepts, familiarity with frameworks such as Transformers, PyTorch or TensorFlow
  • Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps
  • Collaborative and humble team player with an ability to work with cross-functional teams, including technical and non-technical stakeholders
  • Passion for learning new skills and staying up-to-date with ML algorithms
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 InformationHealth + 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
  • Flexible Working: MyMode hybrid-working model with Flex, Office Based, and Remote options (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 upskill 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!


#J-18808-Ljbffr

Related Jobs

View all jobs

Machine Learning Scientist II

Machine Learning Scientist III

Machine Learning Scientist III – Experimentation Science (Statistical Methodologies)

Machine Learning Scientist (with Structure-based Experience)

Machine Learning Scientist II

Machine Learning Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.