I am an AI Team Lead and Technical Strategist with 8+ years building and scaling AI teams delivering production-ready robotics, computer vision, and ML solutions. I have a proven track record of driving AI roadmaps, growing teams, and delivering measurable business impact across industries. Driven by interesting challenges and off-the-shelf solutions, I am fluent in English and Turkish, and conversational in German and Bulgarian. I enjoy collaborating with stakeholders to align AI solutions with business goals.…

Redzhep M. Redzhebov

I am an AI Team Lead and Technical Strategist with 8+ years building and scaling AI teams delivering production-ready robotics, computer vision, and ML solutions. I have a proven track record of driving AI roadmaps, growing teams, and delivering measurable business impact across industries. Driven by interesting challenges and off-the-shelf solutions, I am fluent in English and Turkish, and conversational in German and Bulgarian. I enjoy collaborating with stakeholders to align AI solutions with business goals.…

Available to hire

I am an AI Team Lead and Technical Strategist with 8+ years building and scaling AI teams delivering production-ready robotics, computer vision, and ML solutions. I have a proven track record of driving AI roadmaps, growing teams, and delivering measurable business impact across industries.

Driven by interesting challenges and off-the-shelf solutions, I am fluent in English and Turkish, and conversational in German and Bulgarian. I enjoy collaborating with stakeholders to align AI solutions with business goals.

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Skills

Experience Level

Object Detection
Expert
Python
Expert
PyTorch
Expert
C
Expert
TensorFlow
Expert
C++
Expert
Docker
Expert

Language

English
Fluent
Turkish
Fluent
German
Intermediate
Bulgarian
Intermediate

Work Experience

AI Team Lead at Unrise Robotics
January 1, 2024 - Present
Developed and implemented the initial computer vision pipelines for ML Ops; developed RL policies for long horizon robot control tasks using Isaac Lab; developed end-to-end synthetic data generation pipeline using Isaac Sim; prototyped zero-shot recognition platform's AI models; researched and improved a 6D pose estimation method for industrial robot operations; oversaw model training processes to ensure high accuracy and efficiency; hired and guided a growing AI team; deployed 6+ robots for different customers; organized workshops and cross-team knowledge sharing; aligned AI solutions with business goals.
Lead AI Engineer & Solutions Architect at KOLEKTOR
June 1, 2022 - December 1, 2023
Architected and managed the development of a full computer vision and deep learning pipeline including active data gathering, auto-annotation, data analytics, algorithm construction, deep model training, optimization, auto model conversion and deployment for multiple clients; designed and implemented end-to-end ROS-based robotic systems; built initial Sim2Real pipelines and auto-translation modules for robot control; led a multi-team effort delivering 20+ niche AI solutions.
Lead AI Engineer at OSTALA AI
April 1, 2019 - June 1, 2022
Architected and managed a full computer vision and deep learning pipeline to handle active data gathering, auto-annotation, data analytics, algorithm construction and deep model training, optimization and deployment for robotic applications; designed semi-automatic data preprocessing and synthetic data generation workflows; led hiring and cross-team collaboration to scale AI capabilities.
Computer Vision & Deep Learning Engineer at SKIDATA GmbH
May 1, 2018 - January 1, 2020
Architected and implemented computer vision and deep learning solutions for robotics and access control systems; led the end-to-end development of CV/ML pipelines and model deployment on ROS-based platforms; collaborated with hardware teams to optimize performance.
Computer Vision & Machine Learning Engineer at Visimagic Inc.
January 1, 2017 - December 1, 2017
Prototyped and deployed automated CV/ML solutions for real-world scenarios including automated object detection and classification; implemented data preprocessing and model evaluation workflows; contributed to a portfolio of domain-specific AI apps.
R&D Engineer at AYVOS
December 1, 2017 - May 1, 2018
Developed and prototyped CV/ML methods; contributed to research-driven product features and data-driven improvements in perception pipelines.
Engineering Intern at Fili Labs Ltd.
July 1, 2015 - October 1, 2015
Accelerated and optimized computer vision library development with CUDA; developed parallel and memory-optimized K-Mer search algorithms; created a new DNA summarization algorithm and a deep recognition method for sequence classification; integrated first version of internal data preprocessing pipeline for online captures.
Engineering Intern at Fili Labs Ltd.
January 1, 2016 - May 1, 2016
Further contributions during a second internship period focusing on data preprocessing, feature engineering and algorithmic improvements within CV/ML pipelines.

Education

Bachelor's degree in Computer Engineering at Yıldız Technical University
September 1, 2013 - December 1, 2017

Qualifications

Deep Reinforcement Learning Nanodegree
January 11, 2030 - January 13, 2026
Fundamentals of Accelerated Computing with CUDA Python
January 11, 2030 - January 13, 2026
AI for Medical Diagnosis
January 11, 2030 - January 13, 2026
Convolutional Neural Networks
January 11, 2030 - January 13, 2026
Introduction to Game Development
January 11, 2030 - January 13, 2026

Industry Experience

Computers & Electronics, Software & Internet, Manufacturing, Professional Services, Media & Entertainment, Other
    paper PLSegmentationPipeline

    https://www.twine.net/signin

    A small and standalone end to end image segmentation pipeline that can be integrated into any mlops. It contains all the tricks that I have used in my past projects to make the semantic segmentation model industrial grade.

    paper PERCy

    https://www.twine.net/signin

    This is the re-implementation of the Prioritised Experience Replay purely in C and also created a small package out of it for the open-source society. The reason of this re-implementation is basically all the raw python implementations are super slow due the slowness of python. Also, the core algorithm boosted using sum-tree data structure to perform very fast and efficient sampling.

    paper MultiMediaSearch

    https://www.twine.net/signin

    This is an extended CLIP like multi-domain search system for the games. It can utilise three different domain and train a custom multi-model network to produce rich cross domain embeddings that will be used in search engines.

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