machine learning engineer for ml platform

Описание

SumUp's Machine Learning Platform team builds foundational tools for data scientists, covering feature engineering, model training, experimentation, monitoring, and serving. Its infrastructure supports models used for fraud detection, lending decisions, and other business and customer protections.

Задачи

• Design and build ML platform tooling for feature engineering, training, experimentation, monitoring, and serving across online and offline use cases
• Simplify feature creation for data scientists by reducing reliance on complex Spark workflows through better abstractions or tooling
• Standardise ML infrastructure and developer experience by replacing fragmented, ad-hoc solutions with scalable, self-service components
• Partner with data scientists to understand their workflows and pain points and translate them into platform improvements
• Mentor data scientists on best practices and drive platform adoption across teams
• Collaborate with Data Platform teams to align ML initiatives with broader data engineering work

Требования

• 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, such as Spark, Flink, or Kafka
• Experience 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

Условия

• €2000 Annual L&D budget for individual development, conferences, or further education
• Corporate pension scheme matching up to 20% of contributions
• 28 Days of paid leave plus public holidays and special leave days
• Urban Sports Club subsidy, Kita placement assistance, and subsidised office lunches
• One-month sabbatical after 3 years of service
• Referral bonus
• Virtual Stock Option programme