Mihail Ivanov, Developer in Sofia, Bulgaria
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Mihail Ivanov

Verified Expert  in Engineering

Bio

Mihail is a back-end developer with 15+ years of experience. He has been working freelance for the last seven years. His primary language is Python, but for the previous year, he also focused on Go. Mihail has led teams developing cutting-edge deep learning solutions, including anomaly detection in people's behavior in public places, high-speed defects detections in production lines with edge devices, and recommendation systems for social networks.

Portfolio

Muplex Technologies
Python 3, Django, Flask, C++, Go, Cloud Platforms, Engineering, Elasticsearch
Cosense.AI
Python 3, OpenCV, TensorFlow, PyTorch, Artificial Intelligence (AI)...
Data Suisse
Node.js, Python 3, Supervised Learning, Vue, Elasticsearch

Experience

  • Python 3 - 10 years
  • APIs - 10 years
  • Machine Learning - 3 years
  • Artificial Intelligence (AI) - 3 years
  • Edge TPU - 3 years
  • Deep Learning - 3 years
  • OpenCV - 3 years
  • Go - 1 year

Availability

Part-time

Preferred Environment

Python 3, Go, APIs, Artificial Intelligence (AI), Machine Learning, Fintech

The most amazing...

...thing I've worked on is an automated detection system for public places, which detects visual anomalies in people's behavior to prevent incidents.

Work Experience

Founder

2015 - PRESENT
Muplex Technologies
  • Led a team for video recommendations on a social network.
  • Developed an automated monitoring system for missing products on shop shelves.
  • Set up and supported big data social network processing with Python and NoSQL.
  • Developed software for cash registers and EMV-compatible POS/EFT terminals.
  • Created a fraud detection system for online payment systems.
Technologies: Python 3, Django, Flask, C++, Go, Cloud Platforms, Engineering, Elasticsearch

Managing Partner and CTO

2020 - 2021
Cosense.AI
  • Led a team that developed people's behavior anomaly detection in crowded environments (multi-object tracking, multi camera person re-identification, appearance analysis, pose estimation).
  • Managed a team that developed anomaly and defects detection in production lines (Coral services framework, Jetson TX2, and Nano).
  • Developed facial recognition and an ID/passport matching and validation system.
Technologies: Python 3, OpenCV, TensorFlow, PyTorch, Artificial Intelligence (AI), Machine Learning, Go, Cloud Platforms, Engineering, Elasticsearch

CTO

2019 - 2020
Data Suisse
  • Developed data deduplication, validation, and cleaning of algorithms.
  • Researched the latest achievements in transfer learning to handle unseen before data.
  • Automated processing and deduplicating personal data for collector companies in Germany.
Technologies: Node.js, Python 3, Supervised Learning, Vue, Elasticsearch

Lead C++ Developer/Lead Python Developer

2011 - 2015
Synergy Global Financial Solutions
  • Developed POS/EFT terminal software. Set up EMV chip, contactless card transactions, and communication with the financial institution.
  • Developed software solutions for clearing and settlement processing between banks.
  • Implemented automated security testing of online applications using Python.
Technologies: C++, C, Python 3, Java, PL/SQL

C/C++ Developer

2009 - 2011
Instinctiv Bulgaria
  • Developed Qt and GUI for mobile application with FFmpeg-based music streaming between devices.
  • Developed instant P2P synchronization between devices.
  • Developed cross-platform embedded applications using C++ and Qt.
Technologies: C++, C, Qt, FFmpeg

C/C++ Developer

2007 - 2009
Opencode Systems
  • Developed a USSD technology server for managing real-time user requests with mobile networks.
  • Developed SMPP communication between mobile servers.
  • Developed an SMPP-based server for processing more than 10,000 short messages per second on a single server instance.
Technologies: C, C++

Experience

Anomaly Detection for Production Lines

Created a high-speed anomaly detection system for production lines, detecting issues with products like:

• Wrong labeling and production information and dates
• Defects in shapes

The system used deep learning on Coral TPU devices to detect and respond with times below 50ms per detection.

Automated Detection of Missing Products on Supermarket Shelves

Developed a deep learning-based application for real-time monitoring of supermarket shelves to detect missing products. I set up integration with external services (Viber API) for staff notification for a fast reaction.

Education

2005 - 2011

Master's Degree in Informatics and Applied Mathematics

University of Sofia - Sofia, Bulgaria

Certifications

MAY 2019 - PRESENT

Deep Learning Specialization

Coursera

Skills

Libraries/APIs

REST APIs, OpenCV, Asyncio, Python Asyncio, SQLAlchemy, TensorFlow, PyTorch, Node.js, Vue, FFmpeg

Languages

Python 3, Python, C++, SQL, Go, C, Java

Paradigms

Object-oriented Programming (OOP), Microservices, Agile, Scrum

Frameworks

gRPC, Django, Flask, Qt

Platforms

Amazon Web Services (AWS), Google Cloud Platform (GCP), Docker

Storage

Databases, NoSQL, Google Cloud, PostgreSQL, Elasticsearch, PL/SQL

Other

APIs, API Integration, Back-end, Back-end Development, Artificial Intelligence (AI), Machine Learning, Deep Learning, Edge TPU, Async/Await, Architecture, Leadership, Financial Software, Fintech, Cloud Platforms, Engineering, Supervised Learning

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