Top Tech Jobs & Startup Jobs in London

Lead the design and deployment of recommendation systems, mentor team members, collaborate across functions, and innovate using emerging ML techniques.

As a Senior Data Enablement Engineer at Depop, you will architect and scale the data platform, develop microservices, and lead initiatives across teams to promote data governance and observability practices.

As an Engineering Manager at Depop, you will lead a cross-functional Payments squad, ensuring the delivery of high-quality solutions, fostering team growth, and collaborating across functions.

The Staff Data Scientist will enhance marketing performance analysis through methodologies like MTA and LTV modeling, while collaborating with senior leadership to drive data-driven strategies.

The role involves leading the Community Experience squad to improve customer support tooling and experiences, managing and guiding engineers while ensuring high-quality delivery and effective collaboration across teams.

The Senior Product Designer will lead end-to-end design for priority web features, collaborating cross-functionally and ensuring a seamless user experience between web and mobile. Responsibilities include designing features for Wallet, Trust & Safety, Shipping, and maintaining design quality.

The People Operations Coordinator will manage HR administration, support employee onboarding/offboarding, assist with payroll, maintain records, and improve HR processes.

The Workplace Manager leads workplace operations and experience, ensuring efficiency, scalability, and excellent employee experiences across offices. Responsibilities include managing teams, projects, vendor relations, and program management.

Join Depop as a Senior Machine Learning Engineer to design and implement ML pipelines for recommendations, collaborating with teams to enhance product personalization.

Depop seeks a Senior Machine Learning Engineer for the Ranking team to develop and maintain machine learning systems for personalized rankings. Responsibilities include designing training pipelines, collaborating with ML scientists, and optimizing model serving systems.