Staff Machine Learning Engineer, Epidemic Sound
2024 — present
Building machine-learning based production systems and prototypes. Focused on agentic discovery systems and search.
About Me
Hi, I’m Daniel Klevebring,
a Staff Machine Learning Engineer at Epidemic Sound in Stockholm, where I work mostly on agentic discovery systems and search.
Before moving into industry, I did a PhD in bioinformatics - which is where I first fell in love with building things from data. These days I build agentic and ML-powered systems using Python, GCP, Kubernetes, and whatever else the problem calls for.
Outside of work, I enjoy playing board games with my wife and kids, cheering on the Hammarby IF women’s football team, and tinkering with side projects.
Senior Machine Learning Engineer, Epidemic Sound
2019 — 2023
Built production systems and prototypes delivering machine-learning based features to end users. Focused on recommender systems and search.
Data Scientist, YDB Technologies AB
2018 — 2019
Built data infrastructure and data-driven features at YDB Tech (subsidiary of Fyndiq).
Data Scientist, Fyndiq
2017 — 2018
Built recommender systems (learning to rank) using neural networks and shallow methods such as matrix factorization with Python.
Senior Bioinformatician, Karolinska Institutet
2014 — 2016
Led development of the bioinformatics pipeline in the Clinical Sequencing of Cancer program.
Postdoctoral Fellow, Science for Life Laboratory
2010 — 2013
Headed the KARMA Tissue study at Karolinska Institutet, coordinating logistics and computational analysis.
Ph.D. in Biotechnology, KTH Royal Institute of Technology
2005 — 2009
Transcriptome analysis, gene expression, massive sequencing, bioinformatics, non-coding RNA, small RNA.