Open to opportunities

Edwin Njakusi

@edwinnjakusi

Message

Machine learning engineer building production-ready LLM and NLP systems.

Kenya

Message

What I'm looking for

I’m seeking roles building production LLM/NLP systems where I can translate business problems into scalable AI solutions, work with modern model stacks and vector DBs, and contribute to CI/CD-driven deployments and rapid prototyping.

I am a machine learning engineer focused on building intelligent, scalable AI systems that automate workflows, improve decision-making, and deliver measurable business impact. I have hands-on experience developing LLM-powered applications, RAG pipelines, vector database integrations, and end-to-end ML pipelines using tools like Python, LangChain, Hugging Face, and FastAPI.

I’ve delivered production projects including a customer feedback analyzer with 92% classification accuracy and a 70% reduction in manual review time, and an AI email support assistant that cut response time by 90%. I prioritize rapid prototyping, strong documentation, and translating business problems into production-ready AI solutions deployed with Docker, CI/CD, and cloud platforms.

Experience

Work history, roles, and key accomplishments

Machine Learning Engineer

Independent / Freelance

Built production-ready LLM and NLP systems including a customer feedback analyzer (92% accuracy) and an AI email assistant that reduced response time by 90%, deploying services with CI/CD and containerized pipelines.

Python Hugging Face fastAPI Docker ChromaDB Pinecone CI CD

AI / ML Student Trainee

Martial Jenga Labs School Of IT

Built and deployed ML models for prediction and classification using TensorFlow and Scikit-learn, designed end-to-end workflows, and documented research-to-deployment processes.

TensorFlow scikit learn Python Pandas Data Cleaning Experimentation