You will get Custom Machine Learning Model Development for Your Business Needs
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Project details
I specialize in developing custom machine learning models tailored to your specific needs, from data preprocessing to model deployment. With over 6 years of experience in AI research and ML engineering, I leverage cutting-edge tools and techniques to deliver scalable, efficient, and highly accurate models. Whether you need a predictive model, computer vision solution, or NLP application, I ensure quality, transparency, and timely delivery.
Machine Learning Tools
BERT, ChatGPT, NLTK, NumPy, OpenCV, Python, Python Scikit-Learn, PyTorch, scikit-learn, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$150
|
Standard
$350
|
Advanced
$750
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 12 days |
Number of Revisions | 0 | 0 | 0 |
Number of Model Variations | 2 | 2 | |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 3 | 5 | 10 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
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About Eyasu
PhD in AI | Machine Learning Engineer| AI Engineer | RAG | AI Agents
100%
Job Success
Addis Ababa, Ethiopia - 12:29 am 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.
Client Purchases & Provides Requirements
Client selects the tier and shares project details (dataset, model preferences).
Model Development & Testing
Develop and train the machine learning model based on the requirements, followed by testing and optimization.