You will get Custom AI Object Detection and Image Classification Pipeline
Top Rated
Project details
Turn your raw imagery and video streams into actionable, high-precision visual data. I engineer and deploy production-ready Computer Vision pipelines specialized in advanced Real-Time Object Detection and Multi-Class Image Classification.
What sets this project apart is a focus on deep technical optimization. Instead of using generic off-the-shelf wrappers, I build end-to-end solutions that handle complex dataset formatting, architecture tuning (including state-of-the-art YOLO models and Vision Transformers), target tracking boundaries, and loss optimization tailored directly to your custom data domains.
Whether you need automated categorical grading, defect detection, or real-time localized target extraction, this solution ensures exceptional accuracy parameters combined with robust MLOps engineering. The final deliverable includes fully tuned inference scripts designed to respect your processing constraints—optimized for low-latency edge deployment or high-throughput cloud cluster execution.
What sets this project apart is a focus on deep technical optimization. Instead of using generic off-the-shelf wrappers, I build end-to-end solutions that handle complex dataset formatting, architecture tuning (including state-of-the-art YOLO models and Vision Transformers), target tracking boundaries, and loss optimization tailored directly to your custom data domains.
Whether you need automated categorical grading, defect detection, or real-time localized target extraction, this solution ensures exceptional accuracy parameters combined with robust MLOps engineering. The final deliverable includes fully tuned inference scripts designed to respect your processing constraints—optimized for low-latency edge deployment or high-throughput cloud cluster execution.
AI Development Type
Deep Learning, Model TuningAI Tools
Keras, OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$250
|
Standard
$450
|
Advanced
$600
|
|---|---|---|---|
| Delivery Time | 4 days | 7 days | 9 days |
Number of Revisions | 3 | 4 | 5 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | - | - | |
Model Documentation | - | ||
Ontology | - | - | |
Source Code | |||
Taxonomy | - | - |
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About Eyasu
PhD in AI | Machine Learning Engineer| AI Engineer | RAG | AI Agents
100%
Job Success
Addis Ababa, Ethiopia - 4:12 pm local time
From LLMs and AI agents to RAG, computer vision, and edge AI, I transform AI concepts into reliable, production-ready solutions.
As a PhD Candidate in Artificial Intelligence and hands-on AI Engineer, I combine advanced AI research with practical engineering to deliver systems that perform beyond the prototype stage.
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🤖 WHAT I BUILD
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▸ AI Agents & Agentic Workflows
▸ Retrieval-Augmented Generation (RAG) Systems
▸ AI Assistants & Intelligent Chatbots
▸ LLM Fine-Tuning & Custom AI Models
▸ Multimodal AI Applications
▸ Computer Vision Systems
▸ OCR & Document Intelligence Solutions
▸ Edge AI & Embedded Intelligence
▸ Custom Machine Learning Solutions
▸ AI-Powered Automation Workflows
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⚙️ WHAT I SPECIALIZE IN
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→ End-to-End AI Development
Research, experimentation, prototyping, deployment, and continuous improvement.
→ Production AI & MLOps
Model deployment, API development, Docker, CI/CD pipelines, monitoring, and scalable infrastructure.
→ AI Optimization & Efficiency
Model compression, quantization, pruning, latency reduction, and efficient inference for resource-constrained environments.
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🚀 FEATURED PROJECT
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NemaNet — Embedded AI for Plant-Parasitic Nematode Detection
Founder and lead AI engineer behind an AI-powered agricultural computer vision system optimized for embedded devices.
Designed, trained, optimized, and deployed deep learning models for accurate, real-time detection on resource-constrained hardware, transforming research into a practical field-ready solution.
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🛠 TECHNOLOGIES
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Programming:
Python • SQL
AI & Deep Learning:
PyTorch • TensorFlow • Hugging Face • Transformers • OpenCV • Scikit-learn
LLMs & Agentic AI:
LangChain • LangGraph • LlamaIndex • OpenAI • Ollama • vLLM
Backend & Deployment:
FastAPI • Docker • Kubernetes • REST APIs • Git • CI/CD
Vector Databases:
FAISS • Pinecone • Qdrant • ChromaDB
Cloud Platforms:
AWS • Azure • GCP
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🎯 WHY CLIENTS WORK WITH ME
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✓ Research-backed AI expertise combined with production engineering experience.
✓ Ability to take projects from initial idea and experimentation to deployment.
✓ Experience building LLM, RAG, Agentic AI, Computer Vision, and MLOps solutions.
✓ Focus on reliable, scalable, and cost-efficient AI systems.
✓ Clear communication and engineering practices designed for long-term success.
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If you need an AI engineer who can bridge advanced AI research with production-ready engineering, I would be happy to discuss your project and help turn your ideas into scalable AI solutions.
Steps for completing your project
After purchasing the project, send requirements so Eyasu can start the project.
Delivery time starts when Eyasu receives requirements from you.
Eyasu works on your project following the steps below.
Revisions may occur after the delivery date.
End-to-End Vision Pipeline Delivery
Complete custom dataset formatting, backbone architecture tuning (YOLO/Transformers), loss optimization, and an inference deployment script matching your latency requirements.