Manuel Precious
@manuelprecious
MLOps and backend engineer building high-performance Python pipelines and scalable machine-learning infrastructure for real-time inference.
What I'm looking for
Building production-ready machine learning pipelines and scalable backend systems. Focused on MLOps, containerization, and automation to turn raw models into stable, highly available software.
Experience
Work history, roles, and key accomplishments
Architected a high-performance behavioral intelligence pipeline ingesting 85,000+ streaming telemetry payloads per minute for real-time inference. Reduced feature-store transformation latency by 35%, implemented MLflow-based deployment/experiment tracking, and improved uptime to 99.9% for distributed prediction microservices.
Machine Learning & Backend Engineer
Skudonet
Oct 2023 - Aug 2024 (10 months)
Built an automated log analysis and anomaly detection pipeline using Python and scikit-learn to isolate system failure patterns. Developed feature-engineering workflows and high-throughput REST APIs to reduce diagnosis time to under 5 minutes and cut database response time by 25%.
MLOps & Distributed Systems Engineer
Skudonet
Aug 2022 - Oct 2023 (1 year 2 months)
Developed load-aware routing and predictive scheduling to orchestrate network packet data arrays across Layer 4/7. Containerized microservices with Docker and implemented CI/CD pipelines, achieving 3x scalability, 99.95% uptime, and 20% lower latency.
Education
Degrees, certifications, and relevant coursework
ISBAT University
Bachelor of Science, Artificial Intelligence & Machine Learning
2022 - 2025
Bachelor of Science in Artificial Intelligence & Machine Learning at ISBAT University in Kampala from 2022 to 2025.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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