MLOps & Data Engineer

• Extensive experience in developing and implementing productive machine learning applications, including model registration, monitoring, and automated deployment processes

• Expert in using Azure, Databricks, Docker, and Terraform for efficient implementation and scaling of ML pipelines, supported by CI/CD methods

• Broad methodological expertise including time series analysis and computer vision, combined with a PhD in Bioinformatics to ensure reproducibility of complex models

• Proven experience collaborating with cross-functional teams to successfully transition machine learning models into productive, scalable systems

Project focus: Predictive Maintenance

• Operation of predictive maintenance applications

• Implementation of prototypical ML models as production code

• Design of object-oriented software architecture

• Creation and maintenance of data preparation and feature engineering pipelines

• Registration and provisioning of ML models

• Evaluation and graphical presentation of model performance

• Creation and automated execution of unit, component, and integration tests

• Code checks and deployment

• Migration of existing production solutions from HDInsight to Databricks

• Automated creation of infrastructure components (IaC)

• Error analysis and troubleshooting in production software operation

• Code reviews

Project focus: supply network simulations

• Development of a simulator for analyzing physical effects in hydrogen supply networks

• Further development of an existing prototype

• Modeling and algorithmic analysis of sample supply networks

• Statistical analysis of time series data

• Development of machine learning models for demand prediction

• Evaluation and graphical presentation of simulation results

• Design of object-oriented software architecture

• Code refactoring and unit test development

Project focus: vegetation management

• Development of an ecological vegetation management solution using machine-learning-based satellite image analysis

• Implementation of image preprocessing functionalities, exploration of augmentation methods for model optimization and development of a custom image registration algorithm

• Creation and configuration of Azure ML pipelines; result validation, runtime analysis, and troubleshooting

• Development of unit tests and code reviews

Project focus: Molecular Fingerprints

• Development of molecular fingerprints and search algorithms in an enzyme database

• Design of new search concepts based on biochemical similarity

• Development and implementation of molecular fingerprints

• PostgreSQL integration of Python/SQL-based stored procedures

• Preparation of validation datasets

• Design, implementation, and evaluation of validation experiments

• Documentation of code and concepts

• Migration of code from test to production environment

• Troubleshooting during database construction

Project focus: Image Processing

• Development of an image processing module within a microservice-based biotechnology software suite

• Code migration from Windows to Linux

• Interface implementation for components of microservice architecture

• Revision and optimization of image processing and clustering algorithms with focus on runtime and memory efficiency

• Design and implementation of testing and validation strategies

• Maintenance and enhancement of software documentation

• Code reviewing