Professional Overview
Are you looking for an independent AI researcher and machine learning engineer? Or a web developer? Or both? With a masters in AI I have learned to not only implement, but also understand and compare algorithms and smart solutions. Regression, classification, natural language processing and many other techniques are well within my comfort zone. Also need an interface or connect it to other services? My web development experience will help you out. I love hearing and digging in to your organization or problem, so reach out!
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Worked with the founder in a two-person technical team and led major workstream
- Co-architected and developed a permission-aware agentic analytics platform that
- Led day-to-day technical development of a spatiotemporal crop-yield and price f
- Built geospatial ingestion and feature pipelines with Python, STAC and Planetary
- Built and operated Dockerized services on Hetzner with GitHub Actions CI/CD and
Key Achievements / KPIs
- Build and deployed production automatic data scientist (agentic) platform
- Build and deployed production crop yield and price forecasting platform.
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Worked with the founder in a two-person technical team and led major workstream
- Co-architected and developed a permission-aware agentic analytics platform that
- Led day-to-day technical development of a spatiotemporal crop-yield and price f
- Built geospatial ingestion and feature pipelines with Python, STAC and Planetary
- Built and operated Dockerized services on Hetzner with GitHub Actions CI/CD and
Key Achievements / KPIs
- Build and deployed production automatic data scientist (agentic) platform
- Build and deployed production crop yield and price forecasting platform.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
