se. Let’s talk

Samuel Edungbola / AI Engineer

Based in Abuja, working globally

From a model
to something useful.

Open to AI engineering roles

I’m Samuel. I build the systems around AI that make it work in the real world, from retrieval and computer vision to the product people actually use.

Explore selected work
LLM systems   /   Retrieval   /   Full-stack ML4+ years building & shipping

01 / Selected work

Ideas, put to work.

A few things I’ve been building.
From voice agents to a Naija match-3 game.

08

Football prediction benchmark

Comparing tabular ML, a neural network, and a fine-tuned LLM with leakage-safe features and calibrated predictions.

Applied machine learning
View all work in detail

02 / Experience

A little of the backstory.

Engineering, ownership, and the
less glamorous work of making things run.

Sep 2025 to PresentCurrent role

Prime Frontier Group

De Facto Chief Technical Officer(CTO)

Technical strategy, ML-driven mineral exploration, and platforms across the group. Reduced external infrastructure costs by 80%.

More about this role
  • Sole owner of technical strategy and architecture across Prime Frontier Group and every subsidiary, covering the full stack of decisions, from platform delivery down to which cloud services get used.
  • Built and lead SAMIS, an ML‑driven mineral‑prospectivity model piloting in Peru, fusing geospatial data with predictive modelling for exploration targeting.
  • Shipped AI chatbots for internal and client‑facing workflows, and drafted a proposal for an LPR + real‑time object‑detection vehicle‑access security system.
  • Re‑architected cloud spend across AWS and Vercel, cutting external infrastructure cost by 80%.
  • Also architect of record for eleven further group platforms: drilling exploration (live), renewable energy, procurement, accounting, and a 41‑person company intranet built end‑to‑end in‑house.
Oct 2025 to PresentConsulting

Kouture Konnect

AI Engineer Consultant

Catalogue-grounded retrieval and recommendations for fashion retail. Retrieval evaluation: 0.79 NDCG, 0.74 MRR, 91% keyword coverage.

More about this role
  • Built a production RAG pipeline using LangGraph, GPT‑4o Nano, text‑embedding‑3‑large, and Chroma, grounding a fashion retailer's chatbot in its own live catalogue instead of generic model knowledge.
  • Recommendation engines for product, design, and stylist discovery, fed by conversion signals and catalogue metadata.
  • Daily automated ingestion pipeline keeping the AI knowledge base in step with an evolving catalogue.
NDCG
0.79
MRR
0.74
Keyword coverage
91%

AI Evaluation Consultant

Alphabet (via Invincible)

Oct 2025 to Nov 2025Remote

  • Rubric‑based evaluation of autonomous agents on complex multi‑step tasks, assessing task completion, factual accuracy, and reasoning efficiency.
  • Reviewed full action trajectories and artefacts to catch hallucinations and reasoning gaps, feeding structured findings back into model and rubric improvements.
Mar 2025 to Jan 2026London · Remote

Pingtop / GreenApps

Senior Machine Learning Engineer

Built ML systems for Tezda as it grew to one million users in five months: feeds, video search, recommendations, and moderation.

More about this role
  • Architected the ML systems behind a growth curve of 100,000 users in 2 months and 1,000,000 in 5, sustaining 80,000 daily actives.
  • Designed a slot‑based feed‑distribution engine with trending, new, following, and item‑based slots, A/B tested for per‑session retention.
  • Built a multimodal moderation pipeline (Falcon NSFW, BERT, Whisper) on AWS EKS at ~99% accuracy with near‑zero false negatives.
  • Fine‑tuned Gemini 2.5 Flash for moderation and for video description/keyword extraction, powering a full video search engine.

Machine Learning Engineer

Mar 2025 to Jun 2025Remote (London)

  • Built Tezda's virality‑prediction engine from TikTok, YouTube, and Instagram signals across 10,000+ videos, comparing early‑phase features against late‑phase viral labels.
  • Neo4j‑backed mutual‑friend and influencer fallback recommendations.
Mar 2022 to Feb 2025The foundations

Earlier experience

Health informatics & backend engineering

Data integrity and reporting at Heartland Alliance Nigeria; core databases, operational APIs, and web development at LifeCare.

More about this role
  • Led EMR database administration and data‑integrity coordination across 9+ facilities on the KP‑CARE 1 project.
  • Power BI dashboards lifted data concurrence 12% and module‑version alignment 45% across 19 facilities.

Backend Engineer

LifeCare

Mar 2022 to Apr 2024Remote

  • Designed the company's core database systems, including access controls guarding personally identifiable information.
  • Built the company website and the general operational APIs the business ran on.

03 / How I work

The whole
system matters.

Away from the keyboard?
Usually at a chessboard.
98th percentile in rapid chess.

The model is one part of the job. I care just as much about the data coming in, the infrastructure underneath, and the experience on the other side.

I work across AI engineering and product development, taking systems from early experiments to production. Based in Abuja, I’ve worked remotely with teams in London and New York.

Models & retrieval
LangGraph, RAG, fine-tuning, Chroma, FAISS
Machine learning
PyTorch, TensorFlow, XGBoost, scikit-learn
Language & vision
Whisper, BERT, spaCy, object detection
Product & infrastructure
Next.js, TypeScript, FastAPI, PostgreSQL, AWS, Docker

Have something in mind?

Let’s make
it work.

Open to roles where I can take an AI system
from the first experiment to the finished product.