04.05.2025 aktualisiert
100 % verfügbar
AI Research Engineer, Machine Learning and Data Science consultant
Reichertshofen, Deutschland
Weltweit
MSc Software EngineeringSkills
Machine learningData ScientistBig DataFull Stack DeveloperArtificial IntelligenceNatural Language UnderstandingData analysisBusiness Analysisdeep learningLarge Language Models (LLMs)
AI Research Engineer with 15+ years of experience, bridging cutting-edge research and business value. Specialized in LLM architectures and neural network optimization.
- AI TRANSFORMATION & STRATEGY: Consulted multiple companies on AI strategy, data science, and finding synergies between their existing tech stack and emerging technologies.
- LLM EXPERTISE: Recent intensive upskilling on LLM-based workflows with APIs under the mentorship of industry leaders. Results included RAG, cross-examination between multiple LLMs, and various tricks that are little known outside of frontier labs.
- DEEP UNDERSTANDING OF NEURAL NETWORKS: Fundamental research funded by the NHR. Created a popular tool for debugging neural networks, making them more interpretable.
- BUSINESS KNOWLEDGE: Startup founder, freelance data science consultant.
- PRACTICAL RESEARCH: Multiple million dollars saved in industry through novel algorithms of my own design, customized for their business needs.
- FULL STACK DEVELOPER: Responsible for the entire tech stack at my startup.
- EXCELLENT CREDENTIALS: Worked at Palantir, received multiple awards and scholarships.
Sprachen
DeutschMutterspracheEnglischverhandlungssicher
Projekthistorie
I helped PWC unify some of their ERP systems and improve them by extending and adding functionalities.
In the process, I advised employees on best practices for coding standards and recommended technologies.
On another project, I helped to integrate our programs with an umbrella project managed by stakeholders in the US, who had very different requirements.
In the process, I advised employees on best practices for coding standards and recommended technologies.
On another project, I helped to integrate our programs with an umbrella project managed by stakeholders in the US, who had very different requirements.
I planned and implemented a data pipeline to merge and clean three separate databases into one, allowing different departments to communicate more effectively. In the process, I sped up bottleneck SQL queries by several orders of magnitude, enabling us to update the data in real time.
I also built a frontend (a Django webserver) to organize and display this data in an understandable manner. This application helps AbbVie's researchers to analyze their data more effectively.
My contract was extended multiple times, as I kept pointing out new ways to utilize the data. I also proposed and then implemented an automated tool to find and visualize possible connections between the disparate data in their legacy databases.
Hopefully my work can help AbbVie in its medical research during the Corona Crisis.
I also built a frontend (a Django webserver) to organize and display this data in an understandable manner. This application helps AbbVie's researchers to analyze their data more effectively.
My contract was extended multiple times, as I kept pointing out new ways to utilize the data. I also proposed and then implemented an automated tool to find and visualize possible connections between the disparate data in their legacy databases.
Hopefully my work can help AbbVie in its medical research during the Corona Crisis.
I developed a tool to improve the robustness of our machine learning models.
Based on my findings there, I proposed, developed and implemented a tool to improve machine learning models, by increasing synergy with internally used simulation software.
I discovered anomalies and irregularities in client data, which exceeded the limitations of existing models. I proposed and implemented modifications to fix our models.