Senior Machine Learning Engineer - Platform Team

Location:

Berlin, Germany |

Employment type:

Office First | Team:
Machine Learning Platform, Data & ML Platform

Team description the company's Machine Learning Platform team builds the foundational tools that every data scientist at the company relies on, from feature engineering and model training through to experimentation, monitoring and serving. Right now, taking a model from idea to production can take months rather than weeks, and that gap has real consequences: it slows down fraud detection, lending decisions, and other models that protect the company's business and its customers.

This role matters because it tackles that bottleneck directly. You'll join a small, high-trust team of ML and ML Ops engineers who sit alongside our Data Streaming and Data Gateway teams, giving you first-hand visibility into how data moves and transforms across the business. If you enjoy turning messy, duplicated tooling into something reliable and self-service, this is a chance to shape infrastructure that touches nearly every model the company runs.

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.

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.

• Opportunity to work with Sum Uppers globally on large-scale fintech products used by millions of businesses worldwide, from our Berlin office. This involves an office-first setup.
• Commitment to Diversity and Inclusion: be part of a workplace that values and promotes diversity, fostering an inclusive environment where everyone's perspectives are respected and embraced.
• Enrolment onto our Virtual Stock Option programme: you will own a stake in the company's future success.
• A dedicated annual L&D budget of €2000 for your individual development, which can be used to attend conferences and/or advance your career through further education.
• A corporate pension scheme where we match up to 20% of your contributions.
• Generous time off: enjoy 28 days of paid leave plus public holidays and special leave days.
• Numerous other benefits such as Urban Sports Club subsidy, Kita placement assistance, subsidised office lunches.
• Break4me: 1-month sabbatical after 3 years of service.
• Referral Bonus: earn additional rewards by referring talented individuals to join the the company team.

About the company

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