Summary
Peter Christiansen is a Senior Computer Vision Engineer with 11 years of experience combining academic research and industrial delivery in autonomous systems, deep learning, and MLOps. He has spent the last two years freelancing at CARIAD (Volkswagen Group) driving active learning pipelines for object detection and semantic segmentation and has a track record of taking models from research to production using ONNX and robust CI/CD practices. His background includes a research postdoc on vision-based underwater navigation and a PhD project on multi-sensor perception for autonomous agriculture, giving him deep domain expertise in real-world, sensor-fusion problems. He favors simple, well-tested code and has built Python-first ML systems with hydra configs, experiment tracking, type-hints, and automated testing to make models reproducible and deployable. Comfortable moving between TensorFlow, PyTorch paradigms and constrained deployments (TFLite, microcontrollers), he blends hands-on model surgery with pragmatic software engineering. Based in Aarhus, Denmark, he brings a research mindset to industrial-scale problems, often surfacing elegant practical solutions that aren’t obvious from papers alone.
11 years of coding experience
5 years of employment as a software developer
Civilingeniør, Teknisk IT, Civilingeniør, Teknisk IT at Aarhus Universitet