14.07.2026 aktualisiert

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Senior AI & MLOps Architect & Technical Lead | Azure, Databricks & KASTEL Security

Heidelberg, Deutschland
Weltweit
M.Sc. Computer Science
Heidelberg, Deutschland
Weltweit
M.Sc. Computer Science

Profilanlagen

Cirriculum_Vitae_without_contact_details_extended.docx

Über mich

I turn AI prototypes into secure, enterprise-grade production systems, derisking under EU AI Act. Backed by KASTEL Security expertise, I act as Technical Lead to elevate Data Science teams and implement robust MLOps frameworks within regulated Enterprise IT In service of Kiechle IT Consulting GmbH.

Skills

APIsMicrosoft AzureBig DataCloud-EngineeringData ArchitecturePythonMachine LearningSQL DeveloperTensorFlowAzure Machine LearningSQLModel Driven ArchitectureData SciencePyTorchLarge Language ModelsApache SparkKeraspandasData LakeScikit-learnKubernetesMachine Learning OperationsDSGVOAzure Data AnalyticsDatabricks
CORE COMPETENCIES & TECHNICAL SKILLS
  1. Machine Learning Engineering (5+ Years):
Expertise in end-to-end model development using Scikit-learn, TensorFlow, Keras, PyTorch.
Specialized in Time Series Forecasting and Event Modeling.
Proficient in Python and Shell scripting for scalable data pipelines.
Regulatory safety via EU AI Act and GDPR (DSGVO).
  1. MLOps & Production Engineering (3.5+ Years):
Design and implementation of CI/CD pipelines for ML models (MLflow, Docker, Kubernetes).
Robust monitoring and alerting architectures using Grafana, API Alerting, and Azure Container Apps (ACA).
Visualization and reporting with Tableau.
  1. Cloud Architecture & Big Data (5+ Years):
Azure Specialist with multi-cloud experience (AWS).
Advanced Data Engineering on Databricks (Lakehouse Architecture).
Strong database management skills: KQL, Oracle, PL/SQL.
  1. Agile Leadership & Process (5+ Years):
Proven track record in agile environments (Scrum) using Jira, Confluence, and Office365 ecosystem.
Focus on bridging the gap between technical execution and business requirements.
Technical Lead for long-term development projects

CERTIFICATIONS & AWARDS
  1. Applied Cybersecurity (KASTEL): Certified by Karlsruhe Institute of Technology (KIT) – Focus on secure AI architecture.
  2. Azure Data Science Associate: Certified Professional.
  3. Azure Fundamentals: Data Engineering, Data Science, Security, Compliance and Identity
  4. (In Progress) Databricks Data Engineering: Associate/Professional
  5. Specialized Training:
Scalable ML on Big Data using Apache Spark.
Modern Forecasting in Practice.
Machine Learning in Trading & Finance.
  1. Public Speaking: Conference Speaker at ICISSP 2022 (International Conference on Information Systems Security and Privacy).
LANGUAGES
  1. German: Native (C2)
  2. English: Full Professional Proficiency (C2)
  3. Spanish: Elementary (A2)
  4. Turkish: Beginner (A1)

Sprachen

DeutschMutterspracheEnglischverhandlungssicherSpanischGrundkenntnisseTürkischGrundkenntnisse

Projekthistorie

Credit check of new customers

Telekommunikation

5000-10.000 Mitarbeiter

Industry: Telco
  1. Position: data scientist, lead developer, team size 4-6, agile scrum
  2. Design of custom documentation structure for component-rich architecture (Jira, Confluence)
  3. Development of a standard for exploratory data analysis
  4. Development in Databricks and Azure (incl. monitoring, alerting, ACA, Docker, KQL)
  5. Model optimization
  6. Software development in Python
  7. PoC for vector-based CosmosDB migration
  8. Stakeholder Management

„PREUNN: Protocol Reverse Engineering using Neural Networks“ 2022, In ICISSP (pp.345-356))

FZI Forschungszentrum Informatik

Internet und Informationstechnologie

50-250 Mitarbeiter

Author of „PREUNN: Protocol Reverse Engineering using Neural Networks“ 2022, In ICISSP (pp.345-356))
Industry: Research, Cybersecurity
  1. Development and research of neural networks in Python and PyTorch
  2. Data analysis with Matplotlib and ML Explainability
  3. Presentation at ICISSP 2022 with best poster award
Joint research work for reinforcement learning + machine learning in IT security.

Credit check of existing customers

Telekommunikation

5000-10.000 Mitarbeiter

Industry: Telco
  1. Development of Big Data ETL pipelines based on common open source frameworks (Apache Hadoop, Apache Hive, Python, Apache Spark, Keras), AWS, Kubernetes, Docker
  2. Development of new functionalities (analytics modules, user feedback and model training processes) for internal analytics platform in Python
  3. Development of SQL and PL/SQL load runs based on specific requirements and storage of the results in SQL databases (Oracle)
  4. Development of models for the detection of anomalies in time series and granular data, event modelling
  5. Development of decision models (e.g. for alarm generation)
  6. Development of causal models for automated root cause analysis
  7. Development of process components for text analysis for the generation of anomaly explanations
  8. Create related dashboards (Tableau)
  9. Creation of monitoring functions (Grafana), as well as documentation

Speech Recognition Bot

Sonstiges

< 10 Mitarbeiter

Industry: Tech Startup
  1. Automatic speech recognition (ASR) using Kaldi (Shell)
  2. Named entity recognition (NER)
  3. Stakeholder management
  4. Software development and operationalization in Python and Docker

Address classification

Transport und Logistik

>10.000 Mitarbeiter

Industry: Logistics
  1. ETL pipeline development with Kedro
  2. REST API with Docker, FastAPI
  3. Data analysis with Matplotlib, Jupyter Notebooks
  4. Software development in Python 3 on Azure

Hercules-2 for predictive maintenance

Institute of Program Structures and Data Organization, KIT (University)

Öffentlicher Dienst

10-50 Mitarbeiter

Industry: Research, Logistics
  1. High-dimensional outlier detection with R, Java
  2. Selection of Data Attributes in Oracle PL/SQL

Zertifikate

Azure Data Science Associate

Microsoft

2025

Introduction to Trading, Machine Learning & GCP

Coursera

2021

Reinforcement Learning for Trading Strategies

Coursera

2021

Scalable ML on Big Data using Apache Spark

Coursera

2021

Using Machine Learning in Trading and Finance

Coursera

2021

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