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ETH Zürich
M.Sc., Computer Science with focus in Visual Computing
January 1, 2009 – January 1, 2011
Sofia University St. Kliment Ohridski
B.S., Computer Science
January 1, 2005 – January 1, 2009
Sofiiska Matematicheska Gimnazia
High School Diploma, Mathematics and English
January 1, 1997 – January 1, 2005
Hedge Fund
Senior Software Engineer
June 1, 2020 – Present
Irvine, California, United States
HyperScience
Director of Engineering (Machine Learning)
April 1, 2019 – March 1, 2020
HyperScience
Head of Machine Learning
January 1, 2017 – April 1, 2019
HyperScience
Machine Learning Engineer
January 1, 2015 – January 1, 2017
SoundCloud
Backend Engineer
November 1, 2012 – August 1, 2014
Sofia, Bulgaria
Software Engineer
October 1, 2011 – November 1, 2012
Zurich
NVIDIA
Software Intern
June 1, 2008 – August 1, 2008
San Francisco Bay Area
MM Solutions
Software Engineer
January 1, 2006 – January 1, 2009
Sofia, Bulgaria
Image compression algorithm:
January 1, 2011 – Present
An image compression algorithm that uses PCA transform to find an image-optimized color space that allows sparse representations in over-complete DCT dictionary. The project was implemented first in Matlab. Later we created a high-performance CUDA implementation.
Iterative Methods for Matrix Factorization with Missing Data (master thesis)
January 1, 2011 – Present
I compared different methods for factorization of large sparsely observed matrices, developed algorithm improvements that significantly reduce the computational complexity of the best method and suggested a prior that improves the results when applied to affine structure-from-motion problems.
Depth from focus/defocus application for N900 phone
January 1, 2010 – Present
An application that extracts depth information from a series of pictures of single scene taken with varying focus distance. The application was implemented on a N900 phone using C++ and QT libraries.
XCS236 - Deep Generative Models
Stanford Online
June 24, 2026 – Present
Functional Programming Principles in Scala
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning research-oriented projects (ETH Zürich thesis), large tech companies (Google, SoundCloud), and startups (HyperScience). The progression into leadership roles in Machine Learning aligns with a growth-oriented culture. However, the target role of 'Data Analyst' seems to be a significant shift from their senior/director-level Machine Learning and Software Engineering roles, which might indicate a mismatch in career trajectory or expectations for the specific role. The projects are highly technical and research-heavy, indicating a strong inclination towards complex problem-solving. The lack of explicit 'Data Analyst' specific projects or experience in the provided data makes it difficult to fully assess cultural fit for that specific role.
Soft Skills & Operational Fit
The candidate's career progression from Engineer to Director of Engineering (Machine Learning) suggests strong leadership, problem-solving, and project management skills. The descriptions of designing and implementing distributed systems indicate a collaborative and strategic approach to complex technical challenges. However, without specific psychometric test results or interview data, a detailed assessment of soft skills and operational fit is limited.