Senior Machine Learning Engineer - Platform Team

About the role

The Machine Learning Platform team builds foundational tools for data scientists, covering feature engineering, model training, experimentation, and serving. This role focuses on eliminating bottlenecks in the ML lifecycle to accelerate fraud detection and lending decisions. You will design and build scalable, self-service infrastructure to improve the developer experience for ML engineers across the business.

Responsibilities

• Design and build ML platform tooling that supports feature engineering, training, experimentation, monitoring, and serving across both online and offline use cases
• Simplify how data scientists create features, reducing reliance on complex Spark workflows through better abstractions or tooling
• Standardise ML infrastructure and developer experience, replacing fragmented, ad hoc solutions with scalable, self-service components
• Partner closely with data scientists to understand their workflows and pain points, translating them into concrete platform improvements
• Mentor data scientists on best practices, helping drive adoption of the platform across teams
• Collaborate with the Data Platform teams to keep ML initiatives aligned with wider data engineering work

Required skills

• Python
• ML infrastructure
• Feature stores
• Orchestration frameworks
• Model serving
• Monitoring systems
• Spark
• Flink
• Kafka
• AWS
• Docker
• Kubernetes
• Terraform

Nice to have

• Metaflow
• MLflow
• Kubeflow
• Tecton
• Chronon
• Airflow

Benefits

• Virtual Stock Option programme
• Annual learning budget
• Corporate pension scheme
• 28 days of paid leave
• Urban Sports Club subsidy
• Kita placement assistance
• Subsidised office lunches
• 1-month sabbatical
• Referral Bonus

About the Company

SumUp is on a mission to empower small businesses across the globe by providing simple and affordable tools that allow them to thrive. Today, over 4 million businesses in 39 markets rely on SumUp as their financial partner to manage payments, finance and customer relationships.