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eCommerce • Social Media
Build, maintain, scale, and improve Depop’s search and recommendation systems serving over one million daily users. Collaborate with product managers, data scientists, mobile, web, and backend engineers to design solutions, write high-quality code, manage workflows and data throughout their lifecycle, and document features. The role includes working with distributed systems, retrieval technologies, databases, message queues, ML-driven systems, testing, DevOps practices, and continuous improvement processes.
Top Skills:
Amazon RedshiftApache KafkaAWSAws AthenaCi/CdDynamoDBElasticsearchJavaOpensearchPostgresPythonRabbitMQScalaVector Retrieval Systems
eCommerce • Social Media
Lead and develop a cross-functional backend and iOS squad focused on trust, safety, and compliance. Own delivery, team health, and product outcomes while balancing user safety, fairness, usability, legal obligations, and technical quality. Drive iteration, experimentation, and measurable impact, engage on architecture and technical trade-offs, unblock decisions, and build an inclusive team culture.
eCommerce • Social Media
Lead strategy and roadmap for Trusted Community to prevent harm across listings, search, and messaging. Own trust signals, risk-based controls, and infrastructure to balance safety with low friction. Partner cross-functionally with Engineering, Trust Detection, Ops, Policy, Legal and CX to reduce counterfeit, scams, and prohibited content while minimising false positives.
eCommerce • Social Media
The Staff Machine Learning Scientist will design, develop, and maintain machine learning models for Depop's fashion resale platform, leading technical initiatives and collaborating across teams to drive innovation in ML solutions.
Top Skills:
AWSAzureDatabricksGCPMachine LearningPysparkPythonPyTorchTensorFlowTransformers
eCommerce • Social Media
Lead Depop's Ranking team to define and deliver ML-driven ranking across Search, Homepage and Recommendations. Set vision and prioritise models, features, infrastructure and experimentation. Partner with ML Engineers, Applied Scientists and product teams to deploy, evaluate and iterate production ranking systems that improve engagement, purchases and marketplace outcomes.
Top Skills:
A/B ExperimentationLearning-To-RankMachine LearningOffline EvaluationProduction MlRecommender SystemsRetrieval SystemsSearch
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eCommerce • Social Media
Join the Platform Core team to design, operate, and automate Depop's AWS-based infrastructure. Build and maintain Terraform/IaC, CI/CD pipelines, Cloudflare edge configurations, and platform tooling using Python/Golang. Mentor engineers, participate on-call, improve security posture, and drive platform reliability and developer self-service.
Top Skills:
AppgateAWSBashCdnCi/CdCloudflareGoHashicorp VaultIacKubernetesLinuxPostgresPythonRestful ApisSystemdTerraformWaf
eCommerce • Social Media
Lead the design and deployment of recommendation systems, mentor team members, collaborate across functions, and innovate using emerging ML techniques.
Top Skills:
PythonPyTorchTensorFlow
eCommerce • Social Media
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.
Top Skills:
AirflowApache KafkaAWSDatabricksMlflowPythonPyTorchRabbitMQSagemakerScikit-LearnSparkTensorFlowTfserving
eCommerce • Social Media
The Senior Data Platform Engineer will architect and build a scalable data platform, enabling teams to manage data with self-serve capabilities using modern tools. Responsibilities include developing microservices, leading technical initiatives, and promoting data governance and observability, collaborating with diverse stakeholders, and mentoring team members.
Top Skills:
AirflowAWSConfluentDatabricksDbtDockerFlinkGCPKafkaAzurePythonScalaTerraform
eCommerce • Social Media
Lead a new Pricing - Buyer Value engineering squad (iOS + backend), own delivery, team health, and cross-functional alignment. Hire and line-manage 4–6 engineers, partner with Product, Design, ML and Analytics, drive experimentation and data-driven decisions, establish ways of working, and foster inclusive culture, coaching, and career growth.
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