(Junior) Machine Learning / MLOps Engineer (m/f/d) - Credit Card

CHECK24 Services GmbH; München; Vor Ort; EUR 45.000 - 80.000; Vollzeit

Zusammenfassung

Ein dynamisches Start-up sucht einen (Junior) Machine Learning / MLOps Engineer, um innovative Lösungen im Fintech-Bereich zu entwickeln. In dieser spannenden Rolle arbeiten Sie eng mit einem talentierten Data Science-Team zusammen, um Machine Learning-Pipelines zu entwickeln und MLOps-Lösungen zu implementieren. Sie profitieren von der Möglichkeit, in einem agilen Umfeld zu arbeiten und Ihre Fähigkeiten in der Datenwissenschaft weiterzuentwickeln. Freuen Sie sich auf eine abwechslungsreiche Tätigkeit, die sowohl kreative als auch technische Herausforderungen bietet, während Sie zur Verbesserung von Empfehlungs- und Ranking-Systemen beitragen. Ein inspirierendes Arbeitsumfeld erwartet Sie, in dem Teamarbeit und Erfolg gefeiert werden.

Leistungen

Catering fünfmal pro Woche

Kostenlose Getränke

Frisches Obst

Cerealien zum Frühstück

Feiern von Erfolgen

Qualifikationen

• Hintergrund in Informatik oder verwandten Bereichen erforderlich.
• Erfahrung mit der Bereitstellung von Machine Learning-Lösungen.

Aufgaben

• Unterstützung bei der Entwicklung und Bereitstellung von Microservices.
• Zusammenarbeit mit dem Team zur Überwachung und Bewertung der Modellleistung.

Kenntnisse

Python

MLOps

SQL (Oracle, PostGres)

NoSQL (MongoDB)

Linux

CICD

Kubernetes

Data Science concepts

Ausbildung

Bachelor in Computer Science

Master in Informatics

Tools

Docker

Sklearn

MLFlow

FastAPI

Jobbeschreibung

About this job

CHECK24 is Germany's largest comparison portal and a dynamic startup in one. In small agile teams, we work daily on more than 50 products to make life easier for our over 15 million customers: We create transparency, make complex products easily understandable, and help consumers save time and money.
As a (Junior) Machine Learning / MLOps Engineer (m/f/d) - Credit Card, you will have the opportunity to gain practical experience while contributing to the development of recommender systems and ranking topics in the Fintech area.

The role focuses on the support of the Data Science team integration with DevOps, with the focus on integrating machine learning solutions into the product. Core responsibilities include development of machine learning pipelines while working closely with the data science, product management, and backend teams. A high level of communication skills is required as well as proficiency in implementing MLOps solutions.
We are looking forward to receiving your application as a (Junior) Machine Learning / MLOps Engineer (m/f/d) - Credit Card at CHECK24 Vergleichsportal Karten & Konten GmbH in Munich.

Your Qualifications

• Background in computer science, informatics, or related fields
• Proficiency in Linux, CICD, and K8 (user level)
• Experience with deployment of machine learning solutions
• Experience in working with on-premise deployment systems
• Experience and proficiency with SQL (Oracle, PostGres) and NoSQL (MongoDB) databases
• Understanding of basic Data Science concepts
• Proficient in Python and familiar with common Data Science stack (Sklearn, MLFlow, FastAPI)

Your Responsibilities

• Familiarity with and affinity for implementing MLOps solutions
• Assist in the design and implementation of machine learning algorithms to enhance our ranking / recommender engine performance
• Support the development and deployment of microservices (Docker, Kubernetes)
• Assist in Data Engineering tasks, such as data warehouse development
• Collaborate with the team to monitor and evaluate model performance, implementing necessary adjustments and improvements
• Enjoy the dynamics of a start-up environment combined with the security of an established online company
• Benefit from the opportunity to collaborate and network with experienced Data Scientists
• We like to celebrate successes together at numerous events
• Catering five times per week with warm lunch. In addition, we provide you with free drinks, fresh fruit, and cereals for breakfast

Contact

Lilly Jacobs
[e-mail]
Send us applications only through our online application form, please. Apply now.