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DevOps​/ML Engineer (m​/f​/d

in 80331, München, Bayern, Deutschland
Unternehmen: Machine Learning Reply GmbH
Vollzeit position
Verfasst am 2026-08-08
Berufliche Spezialisierung:
  • IT/Informationstechnik
    Dateningenieur, Cloud Computing: IT-Infrastruktur & Betrieb, Maschinelles Lernen, Datenwissenschaftler
Gehalts-/Lohnspanne oder Branchenbenchmark: 60000 - 80000 EUR pro Jahr EUR 60000.00 80000.00 YEAR
Stellenbeschreibung
Stellenbezeichnung: DevOps/ML Engineer (m/f/d)

Overview

At Machine Learning Reply, we work with our customers on cutting-edge projects for which we are looking for Dev Ops and ML Engineers to support our customer projects around machine learning and data processing across various industries. To expand our team, we are looking for a talented and highly skilled consultant with a technical background to join our team. As a consultant, you will be responsible for providing expert advice and technical support to our clients.

If you're a Dev Ops or ML Engineer or just starting out in the field of machine learning and/or Dev Ops engineering - if you never lose focus, love coding, data and AI, and are passionate about bringing your ideas to life - then we want to hear from you!

Responsibilities
  • Design innovative, technical approaches for data intensive and applications with a focus on machine learning and artificial intelligence.
  • Implement and take ownership for your solutions on in either cloud based (AWS, Azure or GCP) and/or on-premises infrastructures of our customers.
  • Automate recurring tasks by state-of-the-art Dev Ops and MLOps concepts, enabling your customers to significantly reduce their time-to-delivery.
  • Take care of the necessary monitoring, failover, and recovery infrastructure that allow our customers save operation of their machine learning solutions in agreement with latest regulatory requirements
  • Closely interact with customers and stakeholders to translate concrete and complex business requirements into production-ready solutions
  • Collaborate with various disciplines such as enterprise architects, analysts, data scientists or data engineers to develop data-intensive applications such as data warehouses, data lakes and/or data platforms
What we offer you
  • Access to work on projects across industries (large and mid-market companies in Banking, Insurance, Automotive, Retail, etc.)
  • Broaden your skills through interdisciplinary work and training in the areas of data engineering, cloud architecture, and data science
  • Benefit from industry-leading cooperations in the cloud, BI, and AutoML field
  • Very active social program - including training, conferences, team buildings, Reply Exchange, communities of practices, and hackathons
  • Work in an open, flat environment, within a broad Reply knowledge-sharing network
  • Award-winning office space in downtown Munich with access to “Stammstrecke”
  • You choose your state-of-the-art equipment
  • Public transport ticket with Deutschlandticket
  • Gym-membership subsidy for a gym of your choice
  • Flexible work environment between client, Reply office, and remote work
Minimum

Job Requirements / Qualifications
  • Bachelor’s / master’s degree in computer science or any other related fields (e.g. engineering, statistics, physics).
  • First practical experience with Dev Ops/MLOps principals and computing platforms like Microsoft Azure, AWS and GCP as well as Databricks.
  • Ability to convincingly communicate and present analytical results to management.
  • We cover the full lifecycle of Data, from Cloud Infrastructure, Data Engineering, Data Analytics, and Visualization to ML Engineering to and MLOps. Interest and/or experience in some of those fields is an advantage.
  • Fluent in English and German.
Desired
  • Working experience in cloud technologies (AWS, Azure or GCP), Kubernetes and programming languages like Python, Java and Scala.
  • Practical experience with SQL and No

    SQL database technologies and data lakes
  • Experience with big data technologies (Apache Spark), data streaming (Apache Kafka) and workflow orchestration (Apache Airflow, Dagster)
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