Nejc Ilenic
ML EngineerSenior C++ Developer at GTO Wizard
GTO Wizard
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Senior C++ Developer at GTO Wizard
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Software generalist; I appreciate coherent, well-organized codebases and open engineering discussions over egos.
University of Ljubljana, Faculty of Computer and Information Science
Master's degree, Computer Science
January 1, 2015 – January 1, 2017
University of Ljubljana, Faculty of Computer and Information Science
Bachelor's degree, Computer Science
January 1, 2011 – January 1, 2015
GTO Wizard
Senior C++ Developer
May 1, 2025 – Present
Ljubljana, Slovenia · Remote
BioSort AS
Senior Software Engineer
January 1, 2023 – April 1, 2025
Oslo, Norway
Graphcore
Software Engineer
February 1, 2021 – December 1, 2022
Oslo, Norway
GlobalWebIndex
Machine Learning Engineer
February 1, 2018 – April 1, 2020
Ljubljana, Slovenia
University of Ljubljana, Faculty of Computer and Information Science
Student Member at the Bioinformatics Laboratory
August 1, 2016 – September 1, 2017
Ljubljana, Slovenia
4th Office
Software Developer
August 1, 2015 – August 1, 2015
Ljubljana, Slovenia
IT klinika d.o.o.
Software Developer
July 1, 2014 – August 1, 2015
Ljubljana, Slovenia
fotografi.si
July 1, 2023 – Present
A website for the Slovenian photography community.
Slovenian Tarok card game environment for the OpenSpiel framework
February 1, 2020 – October 1, 2020
A C++ implementation of the Slovenian Tarok card game environment for the OpenSpiel framework.
doddle-model: machine learning in Scala
February 1, 2018 – November 1, 2019
doddle-model is an in-memory machine learning library that can be summed up with three main characteristics: - it is built on top of Breeze - it provides immutable objects that are a doddle to use in parallel code - it exposes its functionality through a scikit-learn-like API
16th place solution for the Intel & MobileODT Cervical Cancer Screening competition on Kaggle
April 1, 2017 – July 1, 2017
The challenge of the competition was to develop an algorithm that accurately identifies a woman’s cervix type based on digital images. Our team ended up 16th out of 848 teams on the private, final leaderboard (top 2%).
Educational Neural Networks Library
February 1, 2017 – August 1, 2017
A pure Python and NumPy implementation of a neural networks library developed for educational purposes.
Orange3 Image Analytics Add-on
October 1, 2016 – September 1, 2017
Orange3 Image Analytics is an add-on for the Orange3 data mining suite (an open-source software). It provides extensions for importing/creating labeled image data sets and embedding them through a variety of pre-trained deep neural networks.
Winning Solution for the Painter by Numbers Competition on Kaggle
August 1, 2016 – October 1, 2016
The challenge of the competition was to examine pairs of paintings and determine whether they were painted by the same artist. Post on the official blog of Kaggle.com: http://blog.kaggle.com/2016/11/17/painter-by-numbers-competition-1st-place-winners-interview-nejc-ilenic/
Domain Independent Monte Carlo Tree Search Methods Implementation
June 1, 2015 – August 1, 2015
A Java implementation of Monte Carlo Tree Search methods that is self-contained and domain-independent. It can easily be used in any state-action domain. The project was developed for my Bachelor’s thesis and is licensed under the terms of the MIT license. CodeReview SE post: http://codereview.stackexchange.com/questions/105009/generic-domain-independent-monte-carlo-tree-search-methods-library
Cultural Fit Analysis
The candidate demonstrates a strong passion for machine learning and computer science through a diverse portfolio of personal projects, including open-source contributions and competitive programming. Their experience spans various companies from startups to larger tech firms (Graphcore), indicating adaptability. The breadth of technologies and problem domains (image analytics, game AI, distributed systems) suggests a curious and versatile individual. The target role of ML Engineer aligns well with their career trajectory and demonstrated interests. However, the lack of explicit team collaboration or cultural values in the provided data limits a deeper cultural fit assessment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-driven individual, evidenced by numerous personal projects and Kaggle competition successes. Experience in leading design and implementation of key components (GlobalWebIndex) suggests leadership potential and ability to drive projects. The description of contributing to PyTorch interfaces and architectural discussions at Graphcore indicates strong collaboration and problem-solving skills within a team setting. However, without specific psychometric or English test results, a detailed assessment of communication clarity, work attitude, stress handling, and team collaboration cannot be fully made.