I am an AI Engineer focused on building AI-native systems. I have trained and deployed traditional ML models for classification, built RAG and agentic workflows into healthcare products, and owned end-to-end lifecycles of AI automations across business workflows. In my spare time I’m developing VISION, a personal multimodal assistant that can perceive my immediate environment, and I enjoy exploring practical AI solutions that make complex processes more efficient and accessible.…

Alechenu Iyoko

I am an AI Engineer focused on building AI-native systems. I have trained and deployed traditional ML models for classification, built RAG and agentic workflows into healthcare products, and owned end-to-end lifecycles of AI automations across business workflows. In my spare time I’m developing VISION, a personal multimodal assistant that can perceive my immediate environment, and I enjoy exploring practical AI solutions that make complex processes more efficient and accessible.…

Available to hire

I am an AI Engineer focused on building AI-native systems. I have trained and deployed traditional ML models for classification, built RAG and agentic workflows into healthcare products, and owned end-to-end lifecycles of AI automations across business workflows.

In my spare time I’m developing VISION, a personal multimodal assistant that can perceive my immediate environment, and I enjoy exploring practical AI solutions that make complex processes more efficient and accessible.

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Skills

Experience Level

Python
Expert
PostgreSQL
Intermediate
Github
Intermediate
Large Language Model
Intermediate
Docker
Intermediate
TypeScript
Intermediate
API
Intermediate
Claude
Intermediate
GitHub Copilot
Intermediate
Product Design
Intermediate
AWS
Intermediate
Redis
Intermediate
C++
Beginner
TensorFlow
Beginner
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Language

English
Fluent

Work Experience

AI Engineer at VISION (Personal Project)
December 1, 2025 - Present
Built a multimodal assistant (voice + live camera) on consumer hardware, unifying streaming ASR, local LLM inference, and real-time TTS. Replaced a dual-model pipeline with a single multimodal model to reduce latency and simplify architecture.
Lead AI Engineer at Meterbolic Ltd, London
November 1, 2025 - Present
Designed and developed MeO, the company's core product, a production-grade multi-agent metabolic health platform built with LangGraph; enabled personalised biomarker interpretation, home test-kit protocol guidance, and practitioner workflow automation. Optimised multi-agent inference with sub-3s p50 latency via Bedrock tuning, prompt caching, and streaming. Built end-to-end LLMOps pipeline spanning indexing, serving, and evaluations, containerised with Docker and served via FastAPI.
AI Engineer at Meterbolic Ltd
June 1, 2025 - November 1, 2025
Designed and deployed full backend infrastructure and frontend: FastAPI app on AWS EC2, Next.js frontend on Vercel, Bedrock-based generation, and Qdrant vector store. Resolved cloud networking, CORS, VPC, and HIPAA-compliance challenges to ship a production-ready beta. Delivered a multi-agent prototype with efficient model selection and prompt caching (32% of credits budget across 9 months).
Intern AI Engineer at Meterbolic Ltd
April 1, 2025 - June 1, 2025
Identified data preprocessing issues causing inconsistent GPT-2 outputs. Built a metabolic health chatbot prototype using Google's Flan-T5 for generation, MiniLM-L6-v2 for embeddings, and FAISS for vector search. Conducted BLEU and ROUGE-F1 evaluations, achieving average BLEU ~0.65 and ROUGE-F1 ~0.78.
Developer at Symptom-to-Condition Classifier
March 1, 2025 - June 1, 2025
Engineered an end-to-end text classification pipeline to classify medical conditions from symptoms. Achieved Macro F1 of 83.4% with a hybrid BioBERT embeddings + LightGBM model, deployed as an interactive Streamlit app.
Backend Software Engineer at Predictive Maintenance & Compliance Assistant
February 1, 2025 - February 1, 2025
Built and integrated the FastAPI backend for a predictive-maintenance and compliance-risk system, connecting XGBoost/LSTM failure-prediction models and an NLP compliance checker into a unified API. Supported real-time monitoring dashboards with failure probabilities, tool-criticality scores, and SHAP-based explanations; co-delivered the final project pitch.

Education

Mechatronics & Robotics Beng at University of Hull
September 25, 2021 - July 17, 2024
Key Modules:- Artificial Intelligence, Computer Vision, and Machine Vision & Sensor Fusion

Qualifications

Add your qualifications or awards here.

Industry Experience

Software & Internet, Healthcare, Professional Services, Other
    Symptom-to-Condition Classifier

    Developed a machine learning model, with the goal of predicting patient conditions(diseases), based on text descriptions. This was a proof-of-concept for classification tasks and not a replacement for doctors.

    MeO- Metabolic health Chatbot

    Led the development of an MVP of a domain-specific chatbot for metabolic health. The system involved developing a RAG pipeline that used a foundation model as the generator model, and scraped data from academic papers, websites and blog posts for the knowledge base, and the result was a Metabolic chatbot grounded in factual knowledge.

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