Janosch Woschitz
Senior Architect, AI ML at BARMER
Berlin, Germany
Summary
🤩
RockstarJanosch Woschitz is a Senior Architect in AI/ML based in Berlin with 14 years of experience designing and delivering large-scale data, analytics and machine learning platforms across enterprise and cloud environments. He has held senior roles at AWS, Cloudera and major engineering organizations, leading architecture for autonomous-driving data platforms and advising clients on production-grade ML and big data solutions. Janosch pairs deep hands-on expertise in Hadoop, Spark, Kafka, SageMaker and cloud-native tooling with a long track record of technical leadership and team enablement. He contributes to notable open-source examples, including Amazon SageMaker notebooks for geospatial workflows (wildfire damage assessment and map-matching), reflecting a practical focus on applied ML at scale. Known for translating complex requirements into reliable, operational systems, he now leads AI/ML architecture at BARMER while continuing to bridge research-grade techniques and production constraints.
14 years of coding experience
17 years of employment as a software developer
German, English, French, Russian
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (14)
spatial10
machine-learning10
jupyter-notebook10
amazon-sagemaker10
geo10
aws10
geospatial10
data-science10
spatial-data10
python9
inference8
deep-learning7
dropwizard6
groovy6
Programming languages (8)
Github contributions (5)
aws/amazon-sagemaker-examples
Feb 2023 - Feb 2024
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠Amazon SageMaker.
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 10 PRs, 1 comment in 1 year
Contributions summary:Janosch contributed to the Amazon SageMaker Examples repository by fixing the download path for source images used in a visualization and adding example notebooks demonstrating SageMaker geospatial capabilities. These notebooks focused on assessing wildfire damage and map-matching, utilizing geospatial data processing techniques. The user's work involved creating and integrating new geospatial functionalities within the SageMaker environment.
pythonjupyter-notebooktrainingawssagemaker
jwoschitz/amazon-sagemaker-examples
Feb 2023 - Feb 2024
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠Amazon SageMaker.
Contributions:42 pushes, 13 branches in 1 year
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