Neven Pičuljan, Developer in Zagreb, Croatia
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Neven Pičuljan

Verified Expert  in Engineering

Deep Learning Developer

Zagreb, Croatia
Toptal Member Since
September 27, 2017

Neven is a passionate deep learning and machine learning research and development engineer with six years of experience. He has extensive experience working with cutting-edge technologies and a solid ability to understand and solve problems efficiently. Neven communicates exceptionally well and is looking for additional freelance projects to challenge himself with.


Pičuljan Technologies
Amazon Web Services (AWS), Flask, SQLAlchemy, PostgreSQL, Git, Apache Kafka...
Toptal Clients
OpenCV, TensorFlow, Caffe, PyTorch, Python
New York-based Company
Python 3, PyTorch, Azure, Machine Learning, Machine Learning Operations (MLOps)




Preferred Environment

Git, PyCharm, Linux, Azure, PyTorch

The most amazing...

...thing I've built is a face recognition system by scraping online data, training the Torch model, and creating a C-based neural network inference engine.

Work Experience

CEO | Founder

2018 - PRESENT
Pičuljan Technologies
  • Researched and wrote scientific research papers that can be seen at and
  • Built an AI library and associated products with the AI library.
  • Created models for time-series analysis, computer vision, and NLP.
Technologies: Amazon Web Services (AWS), Flask, SQLAlchemy, PostgreSQL, Git, Apache Kafka, Docker, C, C++, OpenCV, PyTorch, Python

Artificial Intelligence Specialist

2017 - PRESENT
Toptal Clients
  • Worked on various AI projects (computer vision, time series analysis, NLP, etc.).
  • Implemented computer vision algorithms.
  • Worked with time series data.
  • Implemented a server for AI models.
  • Implemented a data visualization web application.
Technologies: OpenCV, TensorFlow, Caffe, PyTorch, Python

Senior Machine Learning Engineer | Senior Consultant | Senior Partner

2020 - 2023
New York-based Company
  • Conducted research, developed, and deployed multiple machine learning (ML) services, focusing on computer vision and natural language processing (NLP).
  • Tracked and fixed bugs using Jira as a reporting tool.
  • Interviewed and led multiple ML engineers to build ML solutions.
  • Developed, implemented, and deployed AI solutions based on generative AI.
Technologies: Python 3, PyTorch, Azure, Machine Learning, Machine Learning Operations (MLOps)

Machine Learning Engineer

2020 - 2020
NDA (via Toptal)
  • Worked on a text clustering algorithm for an eCommerce project.
  • Contributed to the generation of synthetic text data for training text embedding extractors.
  • Worked on training and evaluating a text embedding extractor.
  • Helped reduce the dimensionality of text embeddings and visualization of text embedding clusters.
Technologies: SpaCy, Matplotlib, Plotly, PyTorch, Scikit-learn, Python

AI Consultant

2020 - 2020
NDA (via Toptal)
  • Consulted for the client on how to create, improve, and deploy an image similarity model.
  • Created a baseline system to perform image similarity estimation.
Technologies: Scikit-learn, Pandas, SciPy, NumPy, PyTorch, Python

AI Developer

2020 - 2020
NDA (Fintech Client; via Toptal)
  • Trained multiple time series analysis models for predicting price behavior in the future.
  • Deployed multiple time series analysis models.
  • Integrated several different finance APIs.
Technologies: Amazon Web Services (AWS), Quandl API, Google Cloud Platform (GCP), Scikit-learn, Pandas, SciPy, NumPy, Theano, TensorFlow, Keras, Python

Computer Vision Developer

2018 - 2019
NDA (Healthtech Client; via Toptal)
  • Trained multiple computer vision models for classification, segmentation, 3D reconstruction, and more.
  • Deployed multiple computer vision models.
  • Organized the protocol for data collection and annotation.
Technologies: Amazon Web Services (AWS), Google Cloud Platform (GCP), Scikit-learn, Pandas, SciPy, NumPy, Open Neural Network Exchange (ONNX), Core ML, OpenCV, Scala, PyTorch, Python

ML/AI Consultant

2017 - 2019
  • Trained different computer vision models for detection, recognition and clustering.
  • Deployed different computer vision models for iOS using CoreML and ONNX.
  • Worked on the protocol for data collection and annotation.
Technologies: Amazon Web Services (AWS), Core ML, Open Neural Network Exchange (ONNX), Scikit-learn, Pandas, SciPy, NumPy, OpenCV, TensorFlow, PyTorch, Python

Co-founder/AI Engineer

2017 - 2019
  • Created a neural network inference engine for Android.
  • Trained a pose estimation model.
  • Created a testing framework for the pose estimation model.
  • Created a pose estimation library in C/C++.
Technologies: C, C++, OpenCV, TensorFlow, Python


2018 - 2018
Fitz-Gerald Research Publications
  • Worked on a web-based application for screening time series data using proprietary algorithms.
Technologies: Amazon Web Services (AWS), SQLAlchemy, Dash, Flask, Scikit-learn, Pandas, SciPy, NumPy, Python

ML Engineer

2018 - 2018
NDA (via Toptal)
  • Created an image/text classifier using PyTorch and a large database.
  • Deployed an image/text classifier on AWS.
  • Created a user interface using Dash by Plotly.
Technologies: Amazon Web Services (AWS), Dash, Scikit-learn, Pandas, SciPy, NumPy, Flask, PyTorch, Python

ML Engineer

2017 - 2017
NDA (via Toptal)
  • Trained neural networks for image similarity.
  • Deployed neural networks for image similarity as a web service.
  • Created a protocol for data collection and annotation.
Technologies: Amazon Web Services (AWS), Dash, Scikit-learn, Pandas, SciPy, NumPy, Flask, PyTorch, Python

Python Django Developer

2017 - 2017
NDA (via Toptal)
  • Worked on a web-shop-like web application.
Technologies: REST APIs, Heroku, PostgreSQL, Django, Python

Research Engineer

2016 - 2017
Visage Technologies
  • Collected the data set for building a face recognition system.
  • Built a training tool and trained a face recognition neural network model using Torch and TensorFlow.
  • Created a testing framework.
  • Coded the neural network inference engine in C/C++.
  • Cross-compiled the neural network inference engine.
Technologies: Android Studio, Robot Operating System (ROS), OpenCV, CLion, PyCharm, Microsoft Visual Studio, BLAS, C++, C, TensorFlow, Torch, PyTorch, Linux

Django Developer

2015 - 2015
Mobilne Aplikacije d.o.o.
  • Developed Django applications and REST web services.
  • Created database models.
  • Scraped data from the internet.
Technologies: MySQL, PyCharm, Django REST Framework, Linux, Python, Django

Machine Learning/Data Mining Intern

2015 - 2015
  • Collected data to create a named entity recognizer for the Croatian language.
  • Trained a named entity recognizer for the Croatian language.
  • Created a testing framework.
  • Made a web service to expose the named entity recognizer.
  • Crawled various types of data from the internet.
Technologies: C++, C, Python, Linux

Software Engineering Intern

2014 - 2014
Visage Technologies
  • Developed a video face annotator.
  • Created tests for the face annotator.
  • Created a user’s manual for the face annotator.
Technologies: Microsoft Visual Studio, OpenCV, C, C++, Windows, Linux

Teaching Assistant on Probability and Statistics

2014 - 2014
University of Zagreb, Faculty of Electrical Engineering and Computing
  • Prepared students for the exams.
  • Created assignments for the students.
  • Corrected students' exams.

Deep Visual Biometrics
Created a feasibility study and demo for a face recognition system that I developed at Visage Technologies. The demo was written in C/C++ and Python. I collaborated with the Swedish Police, the Swedish National Forensic Center, and the Swedish Defence Research Agency on this project.

Neural Network for Function approximation Using Levenberg-Marquardt Algorithm in Torch Framework

A neural network for function approximation using the Levenberg-Marquardt algorithm. I tested the code on various functions and used Torch framework and Python.

Credit Card Application Classifier

A simple classifier in R for credit card applications. I was given a data set with users’ interactions and experimented with various machine learning algorithms: SVMs, decision trees, random forests, logistic regression, etc.


A project in data mining. I was given a data set with detailed information about interactions of visitors with different stations at Copernicus Science Centre in Warsaw, Poland. The goal was to characterize the flow of visitors through these stations and to segment visitors into separate categories/segments. I used R.

Contour Detection

A system for detection and localization of a 2D contour (human head) in an image, where many such contours of different size could exist. For this purpose, I applied the generalized Hough Transform (GHT). The system was written in Python.

Operations on Graphs in LISP

An implementation of various operations on graphs in LISP: finding cycles in graphs, finding paths from one node to another in graphs, checking if the binary tree is symmetric, depth-first order graph traversal, finding maximum depth of a binary tree, and finding a leaf with a maximum value in a binary tree.

Expert System in Prolog

An expert system created in Prolog for animal identification.

Face Recognition

A face recognition system. It was trained and tested in Torch framework. The data set was made of publicly available data sets.

Deep Regression for Face Alignment

Research conducted on different algorithms for face alignment.

Answer Selection in Community Question Answering

A system to automate the classification of Stack Overflow's posts in the answer thread into three categories: One for those that answer the question well. Another for those that can be potentially useful to the user (e.g., because they can help educate him/her on the subject). Lastly, group those that are just bad or useless.

I experimented with various machine learning algorithms (scikit-learn): Gaussian naive Bayes, SVMs, and random forests.

Pedestrian Detection in Urban Environments Using Detectors Based on Contours

A system to do pedestrian detection in urban environments using contour based detection. It was written in Python using Numpy, Scikit-learn, and OpenCV.

Performance-driven Animation as a Web Application

Performance-driven animation as a web application. Face tracking was used to gain motion in the face of an animated virtual character. The graphics system used to build the application was Three.js based on WebGL. The face-tracking system used to build the application was Visage|SDK.

SkyRail Computer Game Controlled with Head Movements
A computer game controlled with head movements. It was written in C# using Unity game engine.


C++, C, Python, R, Lisp, Bash, Prolog, JavaScript, Perl, Java, Scala, Python 2, Python 3


Core ML, Django REST Framework, Django, Caffe, Flask


LSTM, BLAS, TensorFlow, OpenCV, PyTorch, Stanford NLP, Quandl API, SQLAlchemy, NumPy, SciPy, Pandas, Scikit-learn, REST APIs, Keras, Theano, Matplotlib, SpaCy, Python API


Named-entity Recognition (NER), AWS CLI, Microsoft Visual Studio, PyCharm, Android Studio, CLion, Stanford NER, Amazon Elastic Container Service (Amazon ECS), Subversion (SVN), Git, Plotly


Data Science, Management


Amazon EC2, Linux, Amazon Web Services (AWS), Android, Windows, Google Cloud Platform (GCP), Docker, Heroku, Apache Kafka, Azure


Amazon S3 (AWS S3), PostgreSQL, MongoDB, MySQL


Sentiment Analysis, Probability Theory, LSTM Networks, Gated Recurrent Unit (GRU), SVMs, Support Vector Machines (SVM), Random Forests, Decision Trees, Decision Tree Classification, Decision Tree Regression, Logistic Regression, Linear Regression, Classification, Text Classification, Text Analytics, Computer Vision Algorithms, Statistics, Recurrent Neural Networks (RNNs), Natural Language Processing (NLP), Deep Neural Networks, Deep Reinforcement Learning, Reinforcement Learning, Artificial Intelligence (AI), Computer Vision, Deep Learning, Machine Learning, Torch, GPT, Generative Pre-trained Transformers (GPT), Dash, Open Neural Network Exchange (ONNX), Robot Operating System (ROS), Big Data, Machine Learning Operations (MLOps)

2021 - 2023

PhD in Artificial Intelligence

University of Zagreb, Faculty of Electrical Engineering and Computing - Zagreb, Croatia

2015 - 2016

Master's Degree in Computer Science

Warsaw University of Technology - Warsaw, Poland

2014 - 2016

Master's Degree in Computer Science

University of Zagreb, Faculty of Electrical Engineering and Computing - Zagreb, Croatia

2011 - 2014

Bachelor's Degree in Computer Science

University of Zagreb, Faculty of Electrical Engineering and Computing - Zagreb, Croatia


Convolutional Neural Networks



Deep Learning Specialization



Sequence Models



Structuring Machine Learning Projects



Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization



Neural Networks and Deep Learning



Artificial Intelligence

Toptal, LLC


Data Science

Toptal, LLC


Machine Learning


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