Senior Machine Learning Engineer - Platform Team
About the role
Team description
What you'll do
• 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
You'll be great for this role if...
• More than 6 years of experience building production-grade ML infrastructure such as feature stores, training or orchestration frameworks, experimentation platforms, or model serving and monitoring systems
- Strong proficiency in Python and ML libraries.
• Experience with ML orchestration tools such as Metaflow, and familiarity with platform tooling such as MLflow, Kubeflow, Tecton, Chronon, or Airflow
• Solid understanding of batch and real-time data processing patterns, for example Spark, Flink or Kafka
• Comfort working with AWS cloud native services and infrastructure tooling such as Docker, Kubernetes, or Terraform
• Track record of partnering with stakeholders to turn workflow pain points into reusable, self-service platform capabilities
Why you should join SumUp 🌟
About SumUp
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