Job Description
Role
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
You will:
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)
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
You will:
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)
💡 Quick Summary
Seeking a career-building opportunity? The Senior Machine Learning Engineer position is now open for candidates interested in the IT Engineer & Developer Jobs sector. This role in London offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in IT Engineer & Developer Jobs is a plus.
