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Project details
Computer Vision Engineer with 10+ years of experience in Computer Vision and deep learning.
I have experience in creating end-to-end computer vision pipelines using AWS, which includes building the whole machine learning life cycle from:
Data Collection => Data Preprocessing => Model Development & Model Quantization => Deployment.
What I can do for you?
1. Image/Video Classification
2. Object Detection
3. Image Segmentation
4. Activity/Action Recognition
5. Image Super Resolution
6. Style Transfer
7. GAN Celebrity Image Transfer
8. Deep Fakes
9. Emotion Detection
10. Image Captioning/Image Annotation
11. Facial Recognition
I have expertise in the following architectures:
1. CNN
2. LSTM CNN
3. Convolutional LSTM
4. Convolutional Autoencoders
5. GANs
6. YOLO / SSD / Faster R-CNN / Detectron
7. UNET
8. ResNet, AlexNet, VGG16, InceptionV3
9. Siamese Networks
10. 3 CNNs
11. Transformers / ViT
I have expertise in:
1. PyTorch, TensorFlow, Keras, caffe, MXNet
2. ONNX/Tensor RT/TF Light
3. opencv/DLib/mediapipe/huggingface
4. Nvidia CuDNN
5. AWS Sagemaker, EC2, Lambda, S3, ECS, ECR, API Gate Way, & SNS
6. Docker
I have experience in creating end-to-end computer vision pipelines using AWS, which includes building the whole machine learning life cycle from:
Data Collection => Data Preprocessing => Model Development & Model Quantization => Deployment.
What I can do for you?
1. Image/Video Classification
2. Object Detection
3. Image Segmentation
4. Activity/Action Recognition
5. Image Super Resolution
6. Style Transfer
7. GAN Celebrity Image Transfer
8. Deep Fakes
9. Emotion Detection
10. Image Captioning/Image Annotation
11. Facial Recognition
I have expertise in the following architectures:
1. CNN
2. LSTM CNN
3. Convolutional LSTM
4. Convolutional Autoencoders
5. GANs
6. YOLO / SSD / Faster R-CNN / Detectron
7. UNET
8. ResNet, AlexNet, VGG16, InceptionV3
9. Siamese Networks
10. 3 CNNs
11. Transformers / ViT
I have expertise in:
1. PyTorch, TensorFlow, Keras, caffe, MXNet
2. ONNX/Tensor RT/TF Light
3. opencv/DLib/mediapipe/huggingface
4. Nvidia CuDNN
5. AWS Sagemaker, EC2, Lambda, S3, ECS, ECR, API Gate Way, & SNS
6. Docker
What's included
| Service Tiers |
Starter
$500
|
Standard
$2,500
|
Advanced
$5,000
|
|---|---|---|---|
| Delivery Time | 1 day | 7 days | 15 days |
Number of Revisions | 1 | 3 | Unlimited |
Number of Model Variations | 1 | 3 | 10 |
Number of Scenarios | 1 | 3 | 10 |
Model Validation/Testing | - | ||
Model Documentation | - | - | |
Data Source Connectivity | - | - | |
Source Code |
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Nathan K.
Sep 16, 2025
Yolo Unity Project
Working with Jumabek on our Yolo Unity Project was an outstanding experience. His deep expertise in computer vision and AI truly elevated our project beyond initial expectations.
Jumabek demonstrated exceptional technical proficiency in implementing the YOLO object detection framework within Unity, seamlessly integrating complex AI models into our real-time application. His PhD-level knowledge in computer science was evident in his systematic approach to problem-solving and optimization, resulting in a solution that exceeded our performance requirements.
What particularly impressed me was his ability to translate complex technical concepts into practical, production-ready implementations. He not only delivered clean, well-documented code but also provided valuable insights that improved our overall architecture. His experience from leading R&D projects at HumbleBeeAI was clearly beneficial to our project.
Communication was excellent throughout - Jumabek was responsive, proactive in suggesting improvements, and always met deadlines. He demonstrated strong project management skills, keeping us informed of progress and potential challenges well in advance.
I would highly recommend Jumabek for any AI/ML or computer vision projects, especially those requiring integration with game engines or real-time systems. His combination of academic rigor and practical industry experience makes him a rare find on this platform. We're already planning to engage him for future projects.
Jumabek demonstrated exceptional technical proficiency in implementing the YOLO object detection framework within Unity, seamlessly integrating complex AI models into our real-time application. His PhD-level knowledge in computer science was evident in his systematic approach to problem-solving and optimization, resulting in a solution that exceeded our performance requirements.
What particularly impressed me was his ability to translate complex technical concepts into practical, production-ready implementations. He not only delivered clean, well-documented code but also provided valuable insights that improved our overall architecture. His experience from leading R&D projects at HumbleBeeAI was clearly beneficial to our project.
Communication was excellent throughout - Jumabek was responsive, proactive in suggesting improvements, and always met deadlines. He demonstrated strong project management skills, keeping us informed of progress and potential challenges well in advance.
I would highly recommend Jumabek for any AI/ML or computer vision projects, especially those requiring integration with game engines or real-time systems. His combination of academic rigor and practical industry experience makes him a rare find on this platform. We're already planning to engage him for future projects.
JS
Justin S.
Jul 2, 2025
Survey and Planning further for AI VISION STARTUP
About Jumabek
Expert Vetted AI Engineer | Top 1 percent | PhD | 12 years
100%
Job Success
Incheon, South Korea - 6:34 pm local time
⭐ Expert Vetted | Top Rated Plus — Top 1% on Upwork
👨💻 Founder & CEO, HumbleBeeAI
🥇 AI Professor, Gachon University
🏆 PhD in Artificial Intelligence | 12+ years of experience
Short Overview (for a busy client)
I am an AI Engineer, Machine Learning Specialist, and Full‑Stack Developer with 12+ years of experience delivering production-grade AI systems, LLM solutions, intelligent chatbots, and computer vision applications for startups and enterprises worldwide.
I have helped more than 70 companies across the US, Europe, and the Middle East launch scalable AI products and generate over $5M in additional value through automation, predictive systems, and generative AI–driven features.
As Founder & CEO of HumbleBeeAI and AI Professor at Gachon University, I combine deep research expertise with hands-on product delivery, focusing on solutions that are robust, explainable, and directly tied to business KPIs.
If you need someone who can design, build, fine‑tune, and deploy real AI systems—not just prototypes or demos—I can own the full lifecycle from idea to production.
LLMs, Generative AI & Chatbots
LLM fine‑tuning and custom model training (LLaMA, LLaMA‑2, BLOOM, OPT)
Prompt engineering and workflow optimization for reliability and cost-efficiency
RAG systems using LangChain, FAISS, ChromaDB for private / enterprise search
AI chatbot development and multi‑step automation agents
API‑based AI integrations for web and mobile products
Common use cases:
AI assistants, document intelligence, knowledge‑base bots, SaaS AI features, internal productivity tools, and automated business workflows.
Computer Vision Expertise
Object detection and tracking (YOLO, OpenCV, custom deep learning models)
OCR and document-processing pipelines
Face recognition and biometric identification systems
Image segmentation, classification, and visual analytics
Video intelligence pipelines for real-time monitoring and alerts
AR/VR vision‑based applications
Ideal for: industrial monitoring, security and surveillance, retail analytics, document automation, and smart cameras.
Machine Learning & AI Engineering
Predictive modeling and forecasting (churn, demand, risk, pricing)
NLP systems and text analytics
Time‑series modeling and anomaly detection
Reinforcement learning for decision-making and control
Data pipelines and MLOps, CI/CD for ML
AI automation tools and agentic workflows
AI‑powered dashboards and insight products
I prioritize clean data pipelines, reproducible experiments, and scalable deployment from day one.
Full‑Stack & AI Product Development
Frontend: React, Angular, Flutter, Streamlit, Tailwind, Figma
Backend: Node.js, Django, Flask, .NET, REST APIs
Databases: MongoDB, PostgreSQL, MySQL, Firebase, SQL Server
Cloud & DevOps: AWS, GCP, Azure, Docker, Kubernetes, Nginx, Heroku
I can deliver end‑to‑end AI products—from MVP to production at enterprise scale—without heavy dependency on additional engineering teams.
Steps for completing your project
After purchasing the project, send requirements so Jumabek can start the project.
Delivery time starts when Jumabek receives requirements from you.
Jumabek works on your project following the steps below.
Revisions may occur after the delivery date.
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