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Emmanuel Nwosu

Emmanuel Nwosu

Full Stack Developer | Machine Learning Engineer

Talent
Port Harcourt, Port-HarcourtMember since September 16, 2025
ReactPythonDjangoDjango REST FrameworkDockerRenderProblem Solving
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ReactPythonDjangoDjango REST FrameworkDocker

About

Results-driven Full Stack Developer with 5+ years of experience designing, building, and deploying scalable web applications using React and Django, combined with hands-on expertise applying Machine Learning to solve real business problems. Proven track record of delivering end-to-end solutions — from responsive front-end interfaces to robust back-end architecture, RESTful APIs, and ML-powered features — that improve efficiency, user experience, and business outcomes. Adept at working across the full software development lifecycle in fast-paced, collaborative environments.

Experience

Full Stack Developer at Skilicolommy LTD

  • Designed and developed full stack web applications using React and Django, serving [X,000+] active users.
  • Built and maintained 20+ RESTful API endpoints with Django REST Framework, improving data throughput and reducing response times by [X]%.
  • Integrated machine learning models into production systems (e.g. recommendation, prediction, or classification features), increasing [key business metric] by [X]%.
  • Collaborated with cross-functional teams (design, product, QA) in an Agile environment to ship features on a [bi-weekly] release cycle.
  • Optimized application performance and database queries, reducing page load times by [X]%.

Software Developer at Ricks Development LTD

  • Developed responsive front-end interfaces with React, translating UI/UX designs into pixel-perfect, accessible components.
  • Built back-end services and data pipelines in Python/Django to support core product features.
  • Wrote and trained machine learning models to automate [specific task], reducing manual effort by [X] hours/week.
  • Built and containerized a Machine Learning–powered Know Your Customer (KYC) verification service in Python, deployed via Docker for consistent, portable execution across environments.
  • Designed an ML pipeline to automate identity verification through face matching, reducing manual verification time by 89%.
  • Implemented a RESTful API layer to expose verification endpoints, enabling seamless integration with front-end or third-party onboarding systems.
  • Tested the verification pipeline against a sample dataset of identity documents to validate accuracy before deployment.
  • Deployed the service using Docker for reproducible, portable builds, with configuration compatible with cloud or Hugging Face Spaces hosting.

Education

Bachelor's Degree in Computer Science – Clifford University (2021 – 2024)

Skills

Full Stack DeveloperMachine Learning Engineer

Reviews

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