André G. - MLOps, Python, Azure Cloud Engineer

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Kassel, Germany

Experience

Jul 2025 - Aug 2025

2 months

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Schaumann GmbH

Full design, implementation, and operation of a voice chatbot
Evaluation of various implementation approaches (STT, TTS, Speech-to-Speech)
Integration into telephony platforms
Implementation of dashboards & KPIs
Definition and alignment of customer requirements
Technologies used: FastAPI, Deepgram, Elevenlabs, LangChain, LangGraph, GitHub Actions, Streamlit, Vonage

Jun 2025 - Sep 2025

4 months

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Munich RE AG

Developing concepts and migrating GenAI use cases
Defining and migrating role-based access concepts (RBAC) across different cloud environments
Migrating cloud components between AWS & Azure including VNET integration
Technologies used: Azure Entra, Azure DevOps, VNET, Kubernetes, Databricks

Jul 2024 - May 2025

11 months

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E.ON Energy Markets GmbH

Designing & developing an MLOps platform based on Azure ML
Integrating algorithmic energy trading models with exchange trading systems
Creating ETL jobs to run the ML models
Setting up DevOps processes with Azure DevOps
Technologies used: Azure ML, Azure DevOps, Python, Kubernetes

Sep 2023 - Apr 2024

8 months

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Vaillant Group

Developing various data pipelines to transform Apache Kafka data into analytics tables (Delta Tables, MS SQL Server) using PySpark
Designing and creating NoSQL database schemas for big data processing (Data Vault / Data Mart / 3rd Normal Form)
Automating ETL job orchestration with Databricks
Managing data infrastructure in Azure with GitHub Actions, Azure DevOps, and Azure Storage Accounts
Technologies used: Databricks, PySpark, GitHub Actions, Azure Storage Accounts

Mar 2022 - Jul 2024

2 years 5 months

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Munich RE AG

Designing & developing a compliant MLOps solution for the machine learning model lifecycle in reinsurance
Developing solutions for model monitoring
Building a CI/CD system with Azure DevOps pipelines
Implementing centralized logging for multiple Azure services using Azure Monitor
Technologies used: Databricks, Azure DevOps, Kubernetes, Python

Jun 2021 - Jul 2021

2 months

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SMA Solar Technology AG

Automated global economic optimization of production planning with an algorithm (linear programming)
Visualized and presented results to internal stakeholders
Technologies used: Python, python-mip, pandas, jupyter-lab, plotly

Oct 2020 - Feb 2022

1 year 5 months

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SMA Solar Technology AG

Designed and provided technical consulting for implementing the algorithmic trading component of the overall project
Analyzed and quantitatively evaluated backtesting datasets from market price forecast providers
Technologies used: Python, python-mip, pandas, Azure DevOps, Docker

Jul 2020 - Aug 2020

2 months

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SMA Solar Technology AG

Independently designed and conducted a multi-day technical training on data analysis with Python
Technologies used: Python, numpy, pandas, matplotlib, jupyter, scikit-learn

Jan 2020 - May 2020

5 months

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SMA Solar Technology AG

Data-driven forecasting of sales figures for individual product groups based on historical sales data and market development models
Visualized and presented results to internal stakeholders
Technologies used: Python, scikit-learn, prophet, statsmodels, pandas, plotly

Jul 2019 - Dec 2019

6 months

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SMA Solar Technology AG

Introduced a CI/CD process for an operational Python analysis framework with Gitflow-based actions (unit/integration testing, semantic versioning, containerization, deployment)
Implemented using Azure DevOps in a hybrid cloud/on-prem infrastructure
Technologies used: Azure DevOps, Azure Container Registry, Azure Artifacts, Python, Shell Scripts, Ansible, SemVer, Docker

Oct 2018 - Jun 2019

9 months

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SMA Solar Technology AG

Developed a configurable Python framework for performing predictive maintenance analyses and building internal data processing libraries and pipelines
Created expert functions to detect specific faults in photovoltaic inverters
Predicted failure probabilities for individual components based on isotonic regression models
Technologies used: Python, pandas, numpy, scikit-learn, SQLAlchemy, PyArrow

Dec 2015 - Aug 2017

1 year 9 months

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Intelligent Embedded Systems, University of Kassel

Conducted end-to-end machine learning experiment workflows (preprocessing, data filtering, feature engineering, experimental design) for power forecasting of wind turbines (intraday and day-ahead horizons)
Generated parametric and non-parametric density forecasts of power generation
Developed a novel ensemble technique for dynamically weighted combination of individual density forecasts into an ensemble mixture model
Gained basic knowledge in grid simulation as part of an application for BMWi funding
Technologies used: MATLAB, Neural Network Toolbox, Machine Learning Toolbox, Optimization Toolbox, Global Optimization Toolbox

May 2015 - Nov 2015

7 months

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Intelligent Embedded Systems, University of Kassel

Developed an algorithm for event detection in time series based on supervised learning principles
Evaluated the online-capable algorithm using synthetic and real data (e.g., ECG data streams)
Published the developed algorithm on SpringerLink

Summary

Software Engineering (Python): Solid knowledge in designing software frameworks with implemented applications in platform engineering, predictive maintenance, and computer vision.
Cloud Engineering & DevOps: Several years of operating multiple Python software services in native and hybrid cloud environments with Azure DevOps (continuous integration/deployment, containerization, monitoring, etc.) and many Azure services.
Machine Learning, Pattern Recognition, Time Series Forecasting: with implemented applications in predicting the performance of renewable energy, energy market trading, and more.
Energy Forecasting and Trading: PhD in energy forecasting, several years of energy industry background with applications including energy trading.