DevOps/ML Engineer (m/f/d)
At Machine Learning Reply, we work with our customers on cutting-edge projects for which we are looking for DevOps 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 DevOps or ML Engineer or just starting out in the field of machine learning and/or DevOps 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 DevOps and MLOps concepts , enabling your customers to significantly reduce their time-to-delivery.
Take care of the necessary monitoring, failover, and recovery infrastructures 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 .
g. engineering, statistics, physics). First practical experience with DevOps/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 NoSQL database technologies and data lakes Experience with big data technologies ( Apache Spark ), data streaming ( Apache Kafka ) and workflow orchestration ( Apache Airflow, Dagster )