Description

Experienced Data Scientist/Machine Learning Engineer with a focus on Deep Learning. Knowledge and practical experience with all branches of ML - Supervised, Unsupervised and Reinforcement Learning as well as various fields of application. I also taught a course on AI at Karlsruhe University of Applied Sciences.

Languages

German
Native or bilingual
English
Native or bilingual

Workplace preferences

Can work on-site

Berlin (up to 50km), Berlin (up to 50km)

BASF
Freelance Data Scientist/AI Engineer
October 2023 - Today (2 years and 8 months)
○ Designed and implemented Large Language Model (LLM)-based solutions, integrating APIs to deliver intelligent and scalable applications using Azure AI Services and Azure OpenAI.
○ Managed the entire lifecycle of LLM-based products, from proof-of-concept to deployment, leveraging Azure DevOps for CI/CD pipelines, monitoring, and continuous improvements.
○ Developed and optimized API endpoints (FastAPI and Flask) to efficiently serve LLM-powered functionalities, ensuring seamless integration and performance across cloud-native applications on Azure.
○ Led cross-functional teams in building, testing, and deploying LLM-based products.
○ Ensured compliance, security, and cost-effectiveness of LLM products on Azure by implementing best practices in API management, scalability, and monitoring through Azure API Management.
Bayer AG
Backend Engineer
CHEMICAL
July 2023 - October 2024 (1 year and 4 months)
○ Developing LLM-based applications for stakeholders’ decision making
support.
○ In charge of MLOps practices, streamlining the end-to-end machine
learning lifecycle and optimizing the efficiency of model deployment
and monitoring.
○ Established and maintained a robust machine learning model
registry, ensuring systematic cataloging and version control of
models, leading to improved collaboration and knowledge sharing
within the team.
○ Applied extensive AWS expertise to design and implement scalable
and cloud solutions for machine learning workflows, utilizing services
such as Amazon SageMaker, AWS Lambda, and Amazon S3.
○ Implemented Terraform IaC practices on AWS, automating the
deployment and management of machine learning environments,
ensuring consistency and reproducibility across Dev/QA/Prod stages
of the development lifecycle.
MunichRe
AI Engineer
BANKING AND INSURANCE
July 2022 - August 2023 (1 year and 1 month)
○ Created and developed a Neo4j knowledge graph product in a
microservices framework based on Kubernetes.
○ Architecture and schema development, database deployment,
graphql API development and service exposure.○ Implemented knowledge graph algorithms (Graph Neural Networks).
○ Created an MLOps infrastructure (Databricks MLflow based) for
○ productionizing models.
○ Project management for developing a data analytics/MLOps topic.
○ Communication with stakeholders to collect functional and
nonfunctional requirements for the solution.
○ Created and maintained AzureDevops pipelines for CI/CD.
○ Set up integration tests with pytest for quality assurance
○ Set up an inference platform for internal stakeholders.
○ Scrum-based full software development life cycle framework.
○ Language used: Neo4j for graph database. Python, GraphQL and REST
for API deployment.