For us, the employees are in the foreground with their individual goals, ideas and strengths. Thus you proactively shape your career and role. If you can identify with the following position description for the most part, we look forward to receiving your application.
Frameworks for batch and stream processing (eg Apache Spark, Flink, Kafka), experience in working with SQL & NoSQL databases and / or object-based data lakes, machine learning DevOps & deployment (eg dvc, ml-flow, ONNX), Cluster Manager (eg Hadoop YARN, Kubernetes or Mesos) & Automation (eg with Docker or Airflow)
Ideally, touchpoints with ML solutions from major cloud providers like AWS Sagemaker, Google ML Engine or Azure ML Service
Basic knowledge of known ML / AI frameworks (eg Scikit-Learn, Caffe, TensorFlow or Keras)
Knowledge in Python Data Stack (eg Pandas, NumPy, Jupyter Notebook) are welcome but not necessary
Data science techniques and problems, such as Time Series Analysis, Natural Language Processing, Computer Vision, Reinforcement Learning and Feature Engineering, are no stranger to you.