Senior Machine Learning Engineer, Recommendations

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.

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. 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 Machine Learning Engineer to join the Recommendations team in the UK. You will work alongside ML Scientists, Backend Engineers, MLOps and other ML Engineers to build, deploy, maintain, and monitor the machine learning systems that power personalised product recommendations across key surfaces across the app.

• Design and implement pipelines for training, evaluating, deploying, and monitoring retrieval models
• Work closely with ML Scientists to productionise recommendation models, improving reliability, latency, and observability
• Build and optimise embedding generation and recommendations serving
• Partner with backend and product teams to define integration requirements and coordinate deployments of recommendation services
• Help extend the recommendations ML infrastructure in collaboration with MLOps, including maintaining high standards for operational excellence, testing, and incident response
• Contribute to a strong engineering culture focused on scalability, experimentation, and measurable impact

• Proven experience building and deploying ML pipelines in production
• Experience with recommendation, retrieval, or ranking systems (e.g. two-tower models, embeddings, candidate generation)
• Solid understanding of ML workflows from research 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)

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

• Health + Mental Wellbeing: PMI and cash plan healthcare access with Bupa, subsidised counselling and coaching with Self Space, Cycle to Work scheme, 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, 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 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!