Muhammad Dauda
DevOps Engineer at SCIDaR - Solina Centre for International Development and Research
Abuja, Federal Capital Territory, Nigeria
Summary
👤
Senior🎓
Top SchoolMuhammad Dauda is a DevOps engineer with nine years of hands-on experience building cloud-native platforms, AI-driven products, and full-stack systems across Africa. He currently architects and automates scalable, secure infrastructures at SCIDaR, where he built a centralized data repository and an AI platform that processes millions of health data submissions to drive smarter interventions. Skilled in Kubernetes, AWS/GCP, Terraform, ArgoCD and reinforcement learning, he blends MLOps and software engineering to deploy reliable CI/CD pipelines and production ML workflows. His background includes developing logistics and trading systems, demand-prediction pipelines that boosted retail profits, and language-aware NLP models for local contexts—evidence of his ability to turn domain knowledge into measurable impact. Pursuing an MS in Computer Science with research in reinforcement learning, he focuses on smarter automation for complex environments while remaining passionate about efficiency, collaboration, and real-world outcomes.
9 years of coding experience
7 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Bayero University, Kano
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (43)
cracking10
gpgpu9
hashcat9
opencl9
password-recovery9
cuda8
kubernetes7
go7
django-project7
docker7
js6
crud6
django6
html5
sentiment-analysis5
Programming languages (8)
Github contributions (5)
alhajee/GraphQL_with_Django_part2
May 2020 - Dec 2021
A Django Project that covers all the CRUD operations (Create, Read, Update, Delete).
Contributions:3 commits, 2 pushes, 1 branch in 1 year 7 months
cruddjango-project
alhajee/sentiment_analysis_hausa
Nov 2021 - Jan 2023
Sentiment analysis for texts written in Hausa Language
Contributions:43 commits, 6 PRs, 21 pushes in 1 year 2 months
sentiment-analysis
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