Lars Kjeldgaard
Chief Advisor, MLOps Engineer at Udviklings- og Forenklingsstyrelsen
Copenhagen, Capital Region of Denmark
Summary
👤
Senior🎓
Top SchoolLars Kjeldgaard is a seasoned MLOps engineer and chief advisor with nine years of experience building production-ready ML systems for public and media sectors from Copenhagen. He has designed end-to-end MLOps frameworks on AWS with CI/CD for model training, testing and microservice deployment and authored several widely used R and Python packages (e.g., modelgrid, NERDA, senda) that streamline fine-tuning transformers and managing model portfolios. His background in econometrics and award-winning work in financial modelling underpin a pragmatic, metrics-driven approach to fraud detection, housing-price prediction and scalable analytics. Equally comfortable in R and Python, he blends DevOps tooling (Docker, Jenkins, GitHub Actions) with API-driven model serving and reproducible workflows. Notably, he has translated research-grade NLP methods into production tools and spoken at international conferences, reflecting a rare combination of academic rigor and operational delivery.
9 years of coding experience
9 years of employment as a software developer
cand.scient.oecon., Mathematics and Economics, Master Thesis graded 12/12., cand.scient.oecon., Mathematics and Economics, Master Thesis graded 12/12. at Aarhus UniversityMatematisk student, Matematisk student at Viborg Katedralskole
r, sql, English, git, python, docker, bash
Github Skills (40)
caret10
entity10
r-package9
named-entity-recognition9
prepare9
matching9
sequence-labeling9
predictive-modeling9
predictive-analytics9
nlp9
fuzzy-matching8
natural-language-processing8
strings8
transformers8
preprocessing7
Programming languages (4)
Github contributions (5)
smaakage85/shapemaker
Sep 2022 - Dec 2022
Contributions:61 commits, 47 pushes, 1 branch in 3 months
smaakage85/modelgrid
Jun 2018 - Nov 2018
A Minimalistic Framework for Creating, Managing and Training Multiple Caret Models
Contributions:52 commits, 2 PRs, 55 pushes in 4 months
pytorchcaretdeep-learningmachine-learningtraining
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