Janosch Woschitz
Senior ML Engineer at BARMER
Berlin, Germany
Summary
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RockstarJanosch Woschitz is a Senior ML Engineer based in Berlin with 13 years of experience architecting and delivering large-scale data and machine learning systems. He has held senior roles at AWS, Cloudera and DXC where he bridged big-data platforms (Hadoop, Spark, Kafka) with production ML, and led high-performance analytics work for autonomous-driving and other enterprise projects. Technically fluent in Java, Scala and Python, he pairs hands-on implementation with technical leadership in cloud-native environments. He contributed geospatial example notebooks to AWS’s widely used amazon-sagemaker-examples repo — including workflows for wildfire damage assessment and map-matching — illustrating a practical focus on geospatial ML in production. Evolving from web developer to infrastructure and ML lead, he is known for turning complex, data-intensive requirements into scalable, operable solutions.
14 years of coding experience
16 years of employment as a software developer
German, English, French, Russian
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (15)
spatial10
geo10
amazon-sagemaker10
machine-learning10
jupyter-notebook10
aws10
geospatial10
geo-spatial10
spatialdata10
data-science10
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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