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bziamah.tech

Software Engineer · ML ResearcherMSc Computer Science, University of GhanaAccra

Bless
Ziamah

I build production ML systems for fintech and identity, and research robust deep learning for healthcare at DISAL.

Fig. 0: patch attention, ViT-B/16Now: ML for healthcare

98.83%

Accuracy of a fine-tuned ViT-B/16 for SARS detection in chest CT. Peer-reviewed, Springer 2025.

24h → 3m

Customer onboarding time after shipping an ML verification system at Achieve by Petra.

+85%

Verification accuracy from an anti-spoof e-KYC pipeline built at StacAI.

−40%

API calls after a caching redesign at Techvision Global, saving over $400 a month.

01

Focus

A / ML

Scalable AI

Production-grade machine learning pipelines that balance compute efficiency with predictive accuracy, from training and evaluation to serving and monitoring.

B / Systems

Systems Architecture

Modular backends designed for resilience and maintainability: payments, trading and verification systems that hold up at volume.

C / Research

ML for Healthcare

Medical imaging and clinical time-series models that stay reliable under distribution shift, noise and missing data.

Publication · 2025

SARS detection in chest CT scan images using the bootstrapped ViT-B/16 model

Iran Journal of Computer Science · Springer

A fine-tuned ViT-B/16 reaches 98.83% accuracy on 2,482 chest CT images, outperforming DenseNet201 and VGG19.

Read the paper
MSc thesis · In progress

Early sepsis prediction from clinical time series

DISAL, University of Ghana · Advisor: Prof. Justice Kwame Appati

Re-encodes physiological signals as Gramian Angular Field images so CNNs can learn pairwise temporal relationships across whole time windows.

About the thesis
03

Selected work

All projects
Open source · Identity

Anti-Spoof e-KYC System

End-to-end identity verification with built-in spoof detection, improving verification accuracy by 85% for financial services.

TensorFlow · OpenCV · Deep Learning

View on GitHub
Production · Fintech

Customer Onboarding ML Engine

Automated ML verification workflows for new users, cutting onboarding from 24 hours to 3 minutes.

Rails · OpenCV · Face Recognition

Corporate project
Product · Automation

AI Grant Search & Application

A platform that automates grant discovery and applications with AI-powered matching.

Node.js · React · Automation

Visit site
04

Experience

Full history
2025 – Present

Software Engineer

Black Star Group · Onsite

Self-hosted LLM infrastructure, KYC/AML verification backends, and payment and trading integrations for fintech clients.

2024 – Present

Graduate Research Assistant

DISAL, University of Ghana

Thesis research on early sepsis prediction; published work on vision transformers for medical imaging.

2024 – 2025

Software Engineer

Achieve by Petra · Remote

ML-powered identity verification in production (24h → under 3 min) and Rails services automating customer care.

2024 – 2025

Software Engineer, Part-time

Techvision Global (Accede Ltd) · Remote

Next.js and TypeScript interfaces; a caching redesign that cut API calls 40% and saved $400+ a month.

2024

Junior Machine Learning Engineer

StacAI · Remote

End-to-end e-KYC pipeline and anti-spoofing models, improving verification accuracy by 85%.

05

Stack

Machine learning

  • PyTorch
  • TensorFlow
  • scikit-learn
  • Vision Transformers
  • CNNs
  • Computer Vision
  • Anti-spoofing
  • OpenCV
  • Model deployment

Languages & frameworks

  • Python
  • Django
  • FastAPI
  • Ruby on Rails
  • NestJS
  • TypeScript
  • Next.js
  • React
  • Pandas
  • NumPy
  • SQL

Infrastructure & tools

  • AWS
  • GCP
  • Azure
  • Docker
  • PostgreSQL
  • MongoDB
  • Linux
  • Git
  • CI/CD