ml engineer for data-intensive applications

Machine Learning Reply works with customers on machine learning and data processing projects across various industries, providing expert consulting and technical support.

• Design innovative technical approaches for data-intensive applications focused on machine learning and artificial intelligence;
• Implement and take ownership of solutions on cloud-based AWS, Azure, or GCP and/or on-premises customer infrastructures;
• Automate recurring tasks using DevOps and MLOps concepts to reduce customers’ time-to-delivery;
• Develop monitoring, failover, and recovery infrastructure for machine learning solutions in line with regulatory requirements;
• Interact with customers and stakeholders to translate complex business requirements into production-ready solutions;
• Collaborate with enterprise architects, analysts, data scientists, and data engineers to develop data-intensive applications such as data warehouses, data lakes, and data platforms.

• Bachelor’s or master’s degree in computer science or a related field such as engineering, statistics, or physics;
• First practical experience with DevOps/MLOps principles, Microsoft Azure, AWS, GCP, and Databricks;
• Ability to communicate and present analytical results convincingly to management;
• Interest in or experience with data engineering, cloud infrastructure, data analytics, visualization, ML engineering, or MLOps;
• Fluent in English and German;
• Nice to have: working experience with AWS, Azure, or GCP, Kubernetes, Python, Java, Scala, SQL and NoSQL databases, data lakes, Apache Spark, Apache Kafka, Apache Airflow, and Dagster.

• Projects across industries, including Banking, Insurance, Automotive, and Retail;
• Interdisciplinary work and training in data engineering, cloud architecture, and data science;
• Industry-leading cloud, BI, and AutoML partnerships;
• Social program including training, conferences, team buildings, Reply Exchange, communities of practice, and hackathons;
• Open, flat environment within the Reply knowledge-sharing network;
• Award-winning office space in downtown Munich;
• State-of-the-art equipment of choice;
• Public transport ticket with Deutschlandticket;
• Gym-membership subsidy;
• Flexible work environment between client sites, the Reply office, and remote work.