Precious Ikemefuna Azuka
Software Developer
PHP
Python
SQL
JavaScript
TypeScript
Node JS
Active 6 days ago
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Overview
Technical skills
Timeline
Roles
Overview
Computer vision ML engineer (middle) focused on classical image-processing algorithms and small-scale PyTorch model training. The strongest proven skill is robust algorithmic implementation and unit-tested image-processing code as demonstrated by src/image_processing.py together with comprehensive tests in tests/test_image_processing.py. There is limited evidence of large-scale ML engineering practices such as experiment tracking, deployment/serving, GPU-optimized kernels, or original research contributions.
Technical skills
PHP• Junior
Python• Middle
SQL
JavaScript
TypeScript
Node JS• Senior
PHP
Laravel
Python
Django
Flask
Node JS
Sequelize
Express
Axios
Mongoose
Databases
MySQL
PostgreSQL
MongoDB
AI/ML
NumPy
VLM
Deep Learning
AI/ML
LLM
NLP
Frontend
Material UI
React Router
Sass
styled-components
Babel
Tailwind CSS
PostCSS
autoprefixer
React.js
DevOps
CI/CD
Docker
Git
Rest API
AWS
Mobile
React Native
Timeline
Software Engineer (Contract)
•
Middle
Independent Software Development Team (NDA)
•
Contractor
Delivered a multi-module digital operations platform upgrade for a fuel distribution and LPG company, automating payments, order tracking, and financial reporting across departments. Architected a centralized Node.js backend with role-based access control and audit logging, and automated bank-transfer verification using payment gateway integrations, dedicated virtual accounts, and webhook reconciliation. Built React and React Native customer experiences for order tracking, invoicing, notifications, and WhatsApp Commerce onboarding, plus payroll/commission/expense generation to bank-ready CSV files.
Node JS
React.js
React Native
AWS
Artificial Intelligence Engineer
•
Middle
Hayelink Ventures Limited
•
Full-Time
Solely architected Layofa, a MERN SaaS marketplace integrating Google Genkit for virtual try-ons and styling recommendations for African fashion. Designed multi-role marketplace schemas using Mongoose, implemented NLP-driven search and AI styling prompts, and built a usage-metered subscription engine for tiered billing. Secured file handling with AWS S3 presigned URLs and implemented JWT rotation.
Node JSsince 2025
React.jssince 2025
MongoDB
Mongoose
AWSsince 2025
NLP
LLM
Software Engineer
•
Middle
Ficoven Investment Limited
•
Full-Time
Delivered multiple customer-facing platforms spanning fintech, logistics, and government identity services. Contributed to building a Nigerian diaspora NIN pre-enrolment platform and created a fintech payments system with wallets, transfers, bills payments, transaction history, and statement generation. Also built a shipping and logistics platform with tracking and quoting, launched a passports portal for applications and tracking, and developed internal tools to improve the speed and accuracy of data processing.
Yrkeshögskolan Novia (Novia University of Applied Sciences)
Master's Degree •
Industrial Systems Analytics
Middle AI/ML Engineer
Confidence: Medium ML Engineer
Computer vision ML engineer (middle) focused on classical image-processing algorithms and small-scale PyTorch model training. The strongest proven skill is robust algorithmic implementation and unit-tested image-processing code as demonstrated by src/image_processing.py together with comprehensive tests in tests/test_image_processing.py. There is limited evidence of large-scale ML engineering practices such as experiment tracking, deployment/serving, GPU-optimized kernels, or original research contributions.
Model Architecture & Training
3/10
How well models are designed and trained
Practical ML training loop and standard GAN architecture implemented; not research-grade or novel but shows correct use of PyTorch training patterns and device/batch handling.
Data Pipeline & Feature Engineering
2/10
How data is prepared for models
Basic data handling for CSV and MNIST dataset usage present; no large-scale ETL, augmentation pipelines, or leakage controls.
Experimentation & Evaluation
2/10
How results are measured and tested
Unit tests and deterministic examples demonstrate validation and correctness checks; lacks experiment tracking, quantitative eval pipelines, or held-out experiment configs.
MLOps & Deployment
1/10
How models are shipped to production
Minimal MLOps/packaging evidence - project packaging via setup.py; no model versioning, serving, serialization, or monitoring.
Computational Efficiency
2/10
How efficiently computing resources are used
Some attention to device placement and algorithmic complexity; core image operations use straightforward numpy loops without GPU/parallel optimizations or profiling.
Research Depth & Innovation
1/10
Depth of research and new ideas
No evidence of novel research, custom layers, or reproduced paper experiments; implementations are classical algorithms and tutorial-derived GAN code.
Expertise
Computer Vision & Image Analysis• Middle
Industries
Education• Middle
Technologies
AI/ML
Deep Learning
Python• Middle
NLP
VLM
NumPy
LLM
Computer Vision• mentioned only
Vision• mentioned only
Recommendations
- Develop and maintain image-processing and computer-vision utilities or libraries that require clear algorithms and unit tests (filters, edge detectors, pre-processing pipelines).
- Build small to medium ML prototypes and teaching/demo projects using PyTorch (GANs, MNIST experiments, model training notebooks) where correctness and reproducibility matter.
- Implement algorithmic components for systems that need tested graph algorithms and data-structure utilities (routing, pathfinding, adjacency-based features).
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
Junior Backend Developer
Confidence: Low API Engineer
Junior full-stack web developer focused on building basic REST APIs and authentication flows. The strongest proven skill is implementing simple Node.js/Express and Laravel-based authentication, evidenced by react-authentication-jwt/server/package.json and laravel-portfolio/app/Http/Controllers/Auth/*. There is little public evidence of production-grade system design, performance tuning, robust migrations or observability instrumentation.
API Design
2/10
How well APIs are designed
Minimal API design patterns are present (basic Express server and Laravel route/provider files) but mostly framework-generated and lacking explicit versioning, idempotency or pagination designs.
Evidence
react-authentication-jwt/server/src/server.js
react-authentication-jwt/server/package.json
laravel-portfolio/app/Providers/RouteServiceProvider.php
Data Layer & Database
2/10
Working with databases
Data layer artifacts exist (Laravel migrations and a MongoDB dependency) but there is no migration history showing iterative schema evolution or hand-tuned queries.
Evidence
laravel-portfolio/database/migrations/2014_10_12_000000_create_users_table.php
laravel-portfolio/database/migrations/2019_08_19_000000_create_failed_jobs_table.php
react-authentication-jwt/server/package.json
Scalability & Performance
1/10
Handling load and speed
Almost no explicit scalability work; a few references to rate limiting and job tables exist but no caching/invalidation, queue consumers, measured optimizations or connection tuning.
Evidence
laravel-portfolio/app/Providers/RouteServiceProvider.php
laravel-portfolio/database/migrations/2019_08_19_000000_create_failed_jobs_table.php
System Architecture
1/10
Overall system structure
Project layout follows standard framework structure which shows familiarity with common boundaries but no deliberate service decomposition or documented architecture trade-offs.
Evidence
laravel-portfolio/app/Http/Controllers/Auth/RegisteredUserController.php
laravel-portfolio/app/Providers/AppServiceProvider.php
Security & Auth
2/10
Protecting data and access
Authentication and basic security patterns are present (auth controllers, LoginRequest with RateLimiter and Sanctum in composer) indicating awareness of auth concerns, but token lifecycle, revocation, input hardening and other advanced controls are not shown.
Evidence
laravel-portfolio/app/Http/Controllers/Auth/AuthenticatedSessionController.php
laravel-portfolio/app/Http/Requests/Auth/LoginRequest.php
laravel-portfolio/composer.json
Reliability & Observability
1/10
Stability and monitoring
Very limited reliability and observability evidence; default failed_jobs migration and standard error handler stubs exist but there are no structured logs, metrics, retries/backoff, or graceful shutdown implementations visible.
Evidence
laravel-portfolio/database/migrations/2019_08_19_000000_create_failed_jobs_table.php
laravel-portfolio/app/Exceptions/Handler.php
Expertise
Node.js• Junior
Microservices & API Architecture• Junior
Industries
Commerce• Junior
Technologies
PHP• Junior
SQL
Node JS• Senior
MySQL
MongoDB
PostgreSQL
Rest API
Flask
Laravel
CI/CD
Django
Git
AWS
Docker
Mongoose
Sequelize
Laravel• mentioned only
Recommendations
- Assign to build or extend small REST APIs and auth flows (Node.js/Express or Laravel) including endpoints, basic rate limiting and token handling.
- Develop single-service e-commerce features such as cart, checkout and product APIs where framework scaffolding suffices and iterative improvements are possible.
- Work on improving code quality by adding tests, CI pipelines and basic observability (structured logging and simple metrics) before tackling distributed systems or performance critical components.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories:
Junior Frontend Developer
Confidence: Medium App Engineer
Frontend engineer (junior) focused on React-based frontends and simple full-stack authentication flows - strongest at building small React pages and lightweight server bootstraps. The most proven skill is implementing straightforward React UI and small custom hooks as shown in react-authentication-jwt/client/src/pages/UserInfoPage.js and react-authentication-jwt/client/src/util/useQueryParams.js. There is little evidence of automated tests, production-grade error handling, accessibility engineering, advanced state management, or measured performance optimization.
UI Component Architecture
3/10
How interface parts are built
Basic component structure and a small custom hook; components are simple and mostly local stateful rather than part of a deliberate component system or design-system.
Evidence
react-authentication-jwt/client/src/pages/UserInfoPage.js
react-authentication-jwt/client/src/util/useQueryParams.js
Responsive & Cross-browser
2/10
Works on all screens and browsers
Basic responsive readiness via meta viewport and simple CSS; no advanced layout techniques, RTL, or feature-detection patterns found.
Evidence
react-authentication-jwt/client/public/index.html
react-authentication-jwt/client/src/index.css
Performance Optimization
2/10
Speed of the interface
Minor operational/scale awareness in server start and DB reuse; no measured performance work, code-splitting or virtualization for lists.
Evidence
react-authentication-jwt/server/src/server.js
Accessibility & Semantics
1/10
Usable for everyone
Very limited explicit accessibility work; no ARIA, focus-management, keyboard handling or CI a11y tooling found.
Evidence
react-authentication-jwt/client/public/index.html
react-authentication-jwt/client/src/index.css
State Management & Data Flow
2/10
Managing data in the app
Simple client state with local useState and a small custom hook for query params; no server-state caching, optimistic updates, cancellation or state machines.
Evidence
react-authentication-jwt/client/src/pages/UserInfoPage.js
react-authentication-jwt/client/src/util/useQueryParams.js
react-authentication-jwt/server/src/server.js
UX & Visual Polish
3/10
Look and feel quality
Basic UX polish such as transient success/error messages and simple styling; missing broader UX patterns like skeletons, undo, or progressive loading.
Evidence
react-authentication-jwt/client/src/pages/UserInfoPage.js
react-authentication-jwt/client/src/index.css
Expertise
React• Junior
HTML & CSS• Junior
Technologies
JavaScript
TypeScript
Tailwind CSS
Babel
Express
React.js
Axios
Material UI
Sass
PostCSS
styled-components
React Router
autoprefixer
Recommendations
- Build small to medium single-page applications with React and React Router (forms, client-server auth flows, local hooks).
- Implement CRUD UI features and lightweight back-end endpoints using Express and Node JS (authentication, DB connection reuse).
- Work on accessibility improvements and add basic automated tests to increase production readiness (a11y checks and unit/integration tests).
- Practice state patterns such as request cancellation, optimistic updates and server-state caching in a real app to move beyond local state.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories: