Igor Bakhtikyan, Developer in Gavar, Gegharkunik Province, Armenia
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Igor Bakhtikyan

Verified Expert  in Engineering

Full-stack Developer

Gavar, Gegharkunik Province, Armenia
Toptal Member Since
February 11, 2021

Igor is a full-stack developer with a decade of experience leading and developing projects from scratch to launch, including scope, architecture design, tool stack decisions, and hands-on development. He has deep expertise in C++ and other programming languages, including Python, Tcl, Verilog, Objective-C, and SQL. Igor is known for taking full ownership of projects and collaborating effectively with clients to deliver solutions that exceed expectations.


Agile, Jira, Desktop, Android, iOS, C++, Qt, OpenCV, Darknet, REST, Python...
Anumana, Inc.
C++, Qt, 3D, QML, Python, OpenGL, NVIDIA CUDA, CUDA Kernel...
Tcl, Bash, Linux, Software QA, Verilog




Preferred Environment

Windows, PyCharm, Visual Studio, MacOS, Xcode

The most amazing...

...product I've developed is the autonomous citrus harvester robot software.

Work Experience


2013 - PRESENT
  • Managed a group of developers and defined the technology stack for several projects.
  • Distributed tasks within the team, discovered problems early through standup meetings, and followed the agreed schedules for products in development.
  • Communicated regularly with clients to understand their needs, update them on status and results, and discover problems in the early stages of development.
  • Conducted scientific research on state-of-the-art algorithms and evaluated and validated the resulting articles.
Technologies: Agile, Jira, Desktop, Android, iOS, C++, Qt, OpenCV, Darknet, REST, Python, Detectron, Azure, Databases, NVIDIA CUDA, Git, Computer Vision, FFmpeg, Amazon Web Services (AWS), REST APIs, FastAPI, Flask, Desktop App Development, Microsoft Excel

3D Programmer

2022 - 2024
Anumana, Inc.
  • Implemented a feature that allows for dynamic cutting or sectioning of the heart and artery model based on specified paths to view and study cross-sections of the anatomy at various angles and locations.
  • Provided a user-friendly interface allowing users to specify paths for the anatomical cuts interactively.
  • Profiled and optimized the system's performance, ensuring it remains responsive and efficient, even with the model complexity.
  • Integrated GPU acceleration to improve the performance of the model rendering and updating processes in environments that support GPU computing.
  • Developed an updating mechanism that efficiently updates the anatomical model when the underlying data or model changes.
  • Added multi-model and multi-catheter support to apply several cuts.
Technologies: C++, Qt, 3D, QML, Python, OpenGL, NVIDIA CUDA, CUDA Kernel, Desktop App Development

Software Developer

2010 - 2013
  • Built an automated regression testing framework for internal tools with nightly builds and reporting.
  • Developed a random pattern generation tool for testing memory and BIST wrappers.
  • Developed an end-to-end testing framework for internal tools, memory foundries, and their BIST wrappers. The framework was able to create test scenarios, run them on various grid computing platforms, and analyze reports.
Technologies: Tcl, Bash, Linux, Software QA, Verilog

Synthetic Data Generation

A synthetic data generation tool to enhance machine learning training data. It simulates various scenes, such as city aerial view, road view, and closed areas, and scenarios, such as city traffic, human behavior, and product pipelines. I developed this tool, using AWS and Azure cloud computing platforms to generate data, train new models, and make inferences.


Software for an orange picking robot. The algorithm detects oranges on trees and uses a depth map to send commands to robot motors to pick them. The robot is able to pick an orange within 5-10 seconds. I developed the software, using machine learning to find oranges from camera streams with very high confidence. I also implemented a robot health monitor.

Annotation Tool

Designed and developed a tool for pixel-perfect data annotation that processes image sets and videos for frame-based annotation and extracts data to a network-friendly format. The tool supports DICOM, which allows data annotation for medical images, and data can be uploaded to a data center for training process automation.

Time Tracker App

A time tracking app for macOS, Linux, and Windows. The app can track time spent on tasks, application use, web history, and record screen video during that period. The data collected is sent to a server for later processing. I developed the app on my own.
2009 - 2011

Master's Degree in Informatics and Applied Mathematics

Yerevan State University - Yerevan, Armenia

2005 - 2009

Bachelor's Degree in Informatics and Applied Mathematics

Yerevan State University - Yerevan, Armenia


React, REST APIs, OpenCV, FFmpeg, WinAPI, Xlib, OpenGL


Microsoft Excel, Jira, Git, GNOME, PyCharm, Visual Studio, Xcode


Qt, Unity, Darknet, Cocoa, Flask


C++, Python, Java, JavaScript, Tcl, Bash, Verilog, Objective-C, SQL, QML




Desktop App Development, Agile, REST


Android, iOS, Raspberry Pi, Kernel, Desktop, Azure, NVIDIA CUDA, Linux, Windows, MacOS, Amazon Web Services (AWS)


Image Processing, Computer Vision, Machine Learning, FastAPI, Networking, Discrete Mathematics, Optimization, Game Theory, Graph Theory, Applied Mathematics, Very-large-scale Integration (VLSI), Computer Vision Algorithms, Detectron, Software QA, Artificial Intelligence (AI), APIs, 3D, CUDA Kernel

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