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Machine Learning Engineer

Safaricom PLC

Building real-time ML pipelines for fintech systems serving 50 million customers

• Developed real-time ML pipelines on AWS (SageMaker, S3, EC2) and on-premise using Python, PySpark, and Kafka to process over 5,000 transactions per second, supporting 50 million customers
• Collaborated with cross-functional teams to design and implement feature engineering pipelines for large-scale ML model experimentation and deployment, handling over 10 TB of data weekly
• Integrated LLM and RAG-based approaches into internal tooling to improve feature discovery and retrieval across the team's growing feature store of 10,000+ features
• Engineered scalable data workflows with automated orchestration and CI/CD integration using Python and Jenkins, reducing data processing time by 30%
• Deployed and served ML models using MLRun and Iguazio, leveraging Nuclio serverless functions and Kubernetes pods to deliver low-latency, scalable model inference in production
• Adopted GitHub Copilot as a core part of the development workflow, accelerating pipeline development and improving code consistency across the team

Software Engineer - Fintech

Huawei Technologies

Architected scalable mobile money and digital finance platforms serving 30M+ users

• Designed and deployed scalable architectures for mobile money and digital finance platforms (VOOMA, M-PESA, Cashia, ZIDII) serving over 30 million active users and processing billions of transactions annually
• Improved project efficiency through implementation of Acceptance Test Plans to validate solutions designed, cutting validation time by 25%
• Reduced integration errors by 20% by implementing robust architectural patterns and documentation
• Drafted functional requirement specifications (FRS), configuration requirement documents, and Acceptance Test Plans for over 10 major system functionalities

Backend Software Engineer (Part-time)

Zuyu

Developed secure authentication systems handling 1M+ daily requests

• Developed secure authentication APIs using MERN (MongoDB, Express.js, React and Node.js) stack with TypeScript to handle over 1 million requests per day
• Implemented role-based access control system enhancing platform security and improving compliance, reducing unauthorized access attempts by 25%
• Optimized API performance through caching strategies and database query optimization, reducing average API response time by 30%
• Collaborated with the frontend team to ensure seamless integration with the backend authentication system, reducing integration-related bugs by 15%

Software Service Engineer - Infrastructure

Huawei Technologies

Maintained critical financial infrastructure with 99.999% uptime

• Maintained critical overdraft system with 99.999% uptime through proactive monitoring and optimization, supporting over 1 million daily users
• Implemented automated monitoring and alerting systems for early incident detection, reducing mean time to detection (MTTD) by 30%
• Enhanced system security through regular updates and threat analysis, closing over 10 critical vulnerabilities

Data Analyst (Intern)

Shining Hope For Communities (SHOFCO)

Automated data processing for COVID-19 vaccination optimization

• Automated data processing and reporting using Python, generating over 300 reports to optimize COVID-19 vaccination strategies, saving approximately 20 hours of manual work per week
• Analyzed data trends to support decision-making, contributing to a 2% increase in vaccination rates, leading to over 1,500 additional vaccinations
• Streamlined report generation through process automation, reducing report delivery time by 50%

Software/Machine Learning Engineer - Freelance

Freelancer

Building APIs, CI/CD pipelines, and ML models for various clients

• Designed and integrated APIs, including a custom SMS service using Africa's Talking API and a real-time notification system, bolstering user engagement by 15% and handling over 50,000 notifications daily
• Implemented continuous integration and deployment pipelines with GitHub Actions, automating tests and streamlining client project deployments, reducing deployment time by 40%
• Developed and deployed machine learning models using MLOps best practices with Python, TensorFlow, and MLflow, cutting model deployment time for client applications by 80%

Bootcamp

ALX-Africa (Holberton School)

Software Engineering

BSc

Kenyatta University

Mathematics and Computer Science