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.

Depop is looking for a dedicated Machine Learning Engineer to join our new Core ML team in the UK. You will work alongside ML Scientists, Backend Engineers, and MLOps to build, deploy, maintain, and monitor machine learning infrastructure, such as product matching pipelines, image embedding services, and lightweight classifier deployments, that support multiple product and marketing use cases across Depop.

Responsibilities

• Design and implement pipelines for training, deploying, and monitoring real-time and batch ML models
• Work closely with ML Scientists to productionise models and improve reliability, latency, and observability
• Partner with backend and product teams across Depop to define integration requirements and coordinate deployments of shared ML components
• Help design and extend the ML platform at Depop in collaboration with the MLOps team, across areas such as robust prototyping and training workflows, CI/CD for model deployment, real-time and batch model serving, online/offline feature consistency via our feature store, monitoring and alerting
• Hold high standards for operational excellence, including testing, monitoring, maintainability, and incident response
• Contribute to a strong ML engineering culture focused on scalability, collaboration, and continuous learning

Required Skills And Experience

• Proven track record of building and deploying ML pipelines and contributing to ML platform tooling
• Solid understanding of ML workflows and experience supporting scientists through to production
• Strong ownership mindset and ability to work independently
• Excellent communication skills across technical and non-technical stakeholders
• Experience designing systems in modern cloud environments (e.g. AWS, GCP)

Technologies and Tools

• Python
• ML and MLOps tooling (e.g. SageMaker, Databricks, TFServing, MLflow)
• Common ML libraries (e.g. scikit-learn, PyTorch, TensorFlow)
• Spark and Databricks
• AWS services (e.g. IAM, S3, Redis, ECS)
• Shell scripting and related developer tooling
• CI/CD tools and best practices
• Streaming and batch data systems (e.g. Kafka, Airflow, RabbitMQ)

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

• 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