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.
- AI Engineer
Alechenu Iyoko
- London, United Kingdom
- 2 projects
I am an AI Engineer focused on building AI-native systems.
About
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.
- Joined July 2025
Skills· 14
Languages
- EnglishFluent
Industry experience
- Software & Internet
- Healthcare
- Professional Services
- Other
More experts in London, United Kingdom
Projects · 2
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.
- AI Engineer
Work experience· 6 roles
AI Engineer · VISION (Personal Project)Dec 2025 – Present · 1 yr
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 · Meterbolic Ltd, LondonNov 2025 – Present · 1 yr 1 mo
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 · Meterbolic LtdJun 2025 – Nov 2025 · 6 mos
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 · Meterbolic LtdApr 2025 – Jun 2025 · 3 mos
Developer · Symptom-to-Condition ClassifierMar 2025 – Jun 2025 · 4 mos
Backend Software Engineer · Predictive Maintenance & Compliance AssistantFeb 2025 – Feb 2025 · 1 mo
Education
Mechatronics & Robotics Beng · University of Hull2021 – 2024
Key Modules:- Artificial Intelligence, Computer Vision, and Machine Vision & Sensor Fusion
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