Job
- Level
- Senior
- Location
- Berlin
- Working Model
- Onsite
- Job Field
- IT, Data, DevOps
- Employment Type
- Full Time
- Contract Type
- Permanent employment
Job Summary
In this role, you will design an ML platform that simplifies feature engineering, training, and model monitoring. You will standardize the infrastructure and collaborate closely with data scientists to create effective solutions.
Job Technologies
Your role in the team
- Design and build ML platform tooling that supports feature engineering, training, experimentation, monitoring, and serving across both online and offline use cases.
- Vereinfachen Sie, wie Data Scientists Features erstellen, und reduzieren Sie die Abhängigkeit von komplexen Spark-Workflows durch bessere Abstraktionen oder Tools.
- 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.
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Our expectations of you
Qualifications
- Starke Kenntnisse in Python und ML-Bibliotheken.
- 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.
- Nachweisliche Erfahrung in der Zusammenarbeit mit Stakeholdern, um Workflow-Schmerzpunkte in wiederverwendbare, Self-Service-Plattform-Fähigkeiten umzuwandeln.
Experience
- 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.
- Experience with ML orchestration tools such as Metaflow, and familiarity with platform tooling such as MLflow, Kubeflow, Tecton, Chronon, or Airflow.
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What we offer
- Opportunity to work with SumUppers globally on large-scale fintech products used by millions of businesses worldwide, from our Berlin office.
- This involves an office-first setup.
- Enrolment onto our Virtual Stock Option programme: you will own a stake in SumUp'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 SumUp team.
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Benefits
Work-Life-Integration
Health, Fitness & Fun
Topics You Will Work On
Job Locations
About Your Employer
Sumup
Our mission as a global FinTech company is to build the world's first global card acceptance brand, empowering small businesses all over the world and helping them achieve their goals.
Description
- Language
- English
- Company Type
- Established Company
- Working Model
- Onsite
- Industry
- Internet, IT, Telecommunication
Senior Machine Learning Engineer
- Location
- Berlin
- Working Model
- Onsite
- Diversity
- Open for all genders
- English Only
- English only required
