Koen Vannisselroij

AI Engineer

Berlin, Germany | koen.nissel@gmail.com | linkedin.com/in/koenvannisselroij

Summary

Highly motivated AI Engineer with over 5 years of experience in Data Science and Machine Learning, specializing in the design, development, and deployment of AI-driven automation solutions. Expertise in Natural Language Processing (NLP), Large Language Models (LLMs including GPT-2, OpenAI & Cohere APIs, RAG systems), Deep Neural Networks (DNNs), and Transformers. Proven ability to build and deploy scalable AI solutions across the full stack, integrating ML models into production environments via APIs, utilizing Python, and leveraging cloud platforms like AWS. Passionate about applying cutting-edge AI to solve real-world problems and experienced in collaborating within agile, fast-paced R&D and product-driven teams. Holds a Master's degree in Behavioural Data Science and an AWS Certified Developer certification.

Experience

AI Consultant (Contract)

Undisclosed Company | Remote September 2025 (4-week engagement)

  • Built a sentiment analysis engine that distilled actionable insights from unstructured data streams.
  • Productionised the supporting services through Google Cloud, using gcloud-driven automation to package, deploy, and monitor the stack.

Sabbatical

Personal | Berlin, Germany May 2025 – August 2025

  • Achieved German proficiency at C1 level.
  • Participated in 2 hackathons:
    • Tech:Europe Big Berlin Hack — OPUS track (Winner)
    • Berlin AI Hackathon — Peec AI track (Winner)
  • Pursued personal development, travelling and new hobbies.

AI Engineer

Neople | Amsterdam/Berlin, Netherlands/Germany January 2024 – April 2025 (1 year 4 months)

  • Designed, developed, and deployed NLP-powered automation agents for customer service teams, significantly improving response efficiency and consistency.
  • Engineered full-stack AI solutions, encompassing data pipelines, ML model development (including fine-tuning and evaluation of LLMs for specific automation tasks), and robust production deployment on cloud infrastructure.
  • Implemented and managed APIs for seamless integration of AI models into existing customer service workflows and platforms.
  • Collaborated closely with product and engineering teams in an agile environment to iteratively deliver features, enhance model performance, and ensure solutions met evolving business needs.
  • Took ownership of projects in a fast-moving startup environment, proactively identifying and solving complex technical challenges related to AI system scalability and reliability.

Data Scientist

Xomnia | Amsterdam, Netherlands August 2022 – December 2023 (1 year 5 months total)

Data Scientist - For Technische Unie

November 2022 – December 2023 (1 year 2 months)

  • Developed and implemented machine learning models to optimize inventory management through predictive analytics.
  • Focused on creating scalable and maintainable solutions, contributing to data-driven decision-making processes.

Data Scientist - For Luchtverkeersleiding Nederland (Air Traffic Control)

November 2022 – April 2023 (6 months)

  • Developed a critical machine learning component for a decision support tool aimed at air traffic controllers, focusing on enhancing operational safety and efficiency through predictive modeling.
  • Involved in the research, implementation, and evaluation of ML algorithms suitable for real-time data processing and high-reliability systems.

Data Scientist - Internal Projects & Training

August 2022 – November 2022 (4 months)

  • Delivered external training sessions on data science and machine learning concepts.
  • Contributed to internal R&D initiatives and process improvements.

Machine Learning Engineer

Greenhouse | Eindhoven, Netherlands February 2020 – August 2022 (2 years 7 months)

  • Led and contributed to multiple NLP-focused projects, developing classifiers for clients, but also classification models for internal projects.
  • Managed the end-to-end lifecycle of ML projects, from data acquisition and preprocessing to model training, evaluation, and deployment preparation.

Generative Artificial Intelligence Intern

Greenhouse | Eindhoven, Netherlands September 2019 – January 2020 (5 months)

  • Conducted R&D on cutting-edge Generative AI, including early work with GPT-2, style transfer techniques, and eXplainable AI (xAI).
  • Contributed to research that was co-presented at industry conferences.
  • Co-hosted a PyData workshop on RNN and LSTM for text generation, sharing knowledge with the wider tech community.

Education

M.Sc. Behavioural Data Science

University of Amsterdam (2018-2020)

Grade: 8.0 (German equivalent: 1.3)

B.Sc. Psychology

Maastricht University (2014-2018)

Grade: 7.5 (German equivalent: 1.7)

Skills

AI/ML:

AI-driven Automation, Natural Language Processing (NLP), Large Language Models (LLMs: GPT series, OpenAI API, Cohere API, RAG systems), Transformers, Deep Neural Networks (DNNs: Sequence Models, CNNs), Machine Learning (General), Model Implementation, Training/Fine-tuning & Evaluation, API Integration & Development, Data Pipelines, MLOps.

Programming & Best Practices:

Python (Advanced), Clean Coding Principles, Software Engineering Best Practices.

Libraries & Frameworks:

Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers, Langchain, FastAPI, Django REST Framework, Flask.

Platforms & Tools:

AWS (EC2, S3, Lambda, SageMaker etc.), Git & GitHub/GitLab (Version Control, CI/CD Workflows), Docker, CI/CD basics (GitLab CI).

Languages:

Dutch (Native), English (C2), German (C1), Spanish (B1), French (A1).

Certifications & Professional Development

AWS Certified Developer – Associate

Deep Learning Specialization

Mathematics for Machine Learning

Publications

Fotedar, S., Vannisselroij, K., Khalil, S., & Ploeg, B. (2020). Storytelling AI: A Generative Approach to Story Narration. AI4Narratives@IJCAI.