DevOps/ML Engineer (m/f/d)

Role Overview

DevOps/ML Engineer (m/f/d) to support customer projects around machine learning and data processing. You’ll act as a consultant providing technical expertise while designing and implementing cloud and on-prem solutions, with a strong focus on ML, MLOps, and DevOps automation.

Responsibilities

• Design innovative technical approaches for data-intensive applications focused on machine learning and AI.
• Implement and take ownership of solutions on cloud (AWS, Azure, GCP) and/or on-prem customer infrastructures.
• Automate recurring tasks using DevOps and MLOps practices to reduce time-to-delivery.
• Build and maintain monitoring, failover, and recovery infrastructure for ML systems in line with regulatory requirements.
• Translate business requirements into production-ready solutions through close interaction with customers and stakeholders.
• Collaborate with architects, analysts, data scientists, and data engineers to develop data platforms such as:
  • Data warehouses
  • Data lakes
  • Data platforms

Requirements

• Bachelor’s or master’s degree in computer science or related fields (e.g., engineering, statistics, physics).
• First practical experience with DevOps/MLOps and computing platforms like Azure, AWS, GCP, plus Databricks.
• Ability to communicate and present analytical results to management.
• English and German fluency.
• Interest/experience in parts of the data lifecycle is an advantage.

Nice to Have

• Working experience with cloud technologies (AWS/Azure/GCP).
• Kubernetes experience.
• Programming languages such as Python, Java, and Scala.
• Practical experience with SQL and NoSQL databases and data lakes.
• Big data and streaming/orchestration tools:
  • Apache Spark
  • Apache Kafka
  • Apache Airflow or Dagster

Work Model / Location

• Based in Munich with a flexible work environment between client site, Reply office, and remote work.