I am a data and AI engineer focused on delivering machine learning solutions that balance technical rigour with practical deployment. I hold an MSc in Artificial Intelligence and Machine Learning from the University of Limerick and have applied my skills across cloud platforms including AWS, Azure, and GCP. My project work includes developing a defect detection pipeline on AWS Lambda, training deep reinforcement learning agents for Atari, and building a chatbot with LLaMA-2 in Colab. Professionally, I have optimised production quality at Johnson & Johnson using statistical process control and automated KPI reporting at Uganda’s Directorate of Industrial Training using Python and SQL. These experiences have given me a practical understanding of how data pipelines and AI systems operate in real-world settings. I am motivated to advance into mid-level AI/ML roles where I can design, deploy, and optimise machine learning systems.

Jonathan Muwanguzi

I am a data and AI engineer focused on delivering machine learning solutions that balance technical rigour with practical deployment. I hold an MSc in Artificial Intelligence and Machine Learning from the University of Limerick and have applied my skills across cloud platforms including AWS, Azure, and GCP. My project work includes developing a defect detection pipeline on AWS Lambda, training deep reinforcement learning agents for Atari, and building a chatbot with LLaMA-2 in Colab. Professionally, I have optimised production quality at Johnson & Johnson using statistical process control and automated KPI reporting at Uganda’s Directorate of Industrial Training using Python and SQL. These experiences have given me a practical understanding of how data pipelines and AI systems operate in real-world settings. I am motivated to advance into mid-level AI/ML roles where I can design, deploy, and optimise machine learning systems.

Available to hire

I am a data and AI engineer focused on delivering machine learning solutions that balance technical rigour with practical deployment. I hold an MSc in Artificial Intelligence and Machine Learning from the University of Limerick and have applied my skills across cloud platforms including AWS, Azure, and GCP. My project work includes developing a defect detection pipeline on AWS Lambda, training deep reinforcement learning agents for Atari, and building a chatbot with LLaMA-2 in Colab.

Professionally, I have optimised production quality at Johnson & Johnson using statistical process control and automated KPI reporting at Uganda’s Directorate of Industrial Training using Python and SQL. These experiences have given me a practical understanding of how data pipelines and AI systems operate in real-world settings. I am motivated to advance into mid-level AI/ML roles where I can design, deploy, and optimise machine learning systems.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

Data Analyst at Directorate of Industrial Training (DIT)
July 1, 2022 - October 25, 2025
Automated weekly KPI reporting with Python and SQL, reducing preparation time by 40% and enabling senior management to make faster, data-informed decisions across 15 regional centres. Designed secure offline-first workflows during COVID-19 that ensured continuity of national certification programs, allowing 10,000+ candidates to complete exams virtually. Increased data accuracy by 35% by introducing standardised ETL processes and Excel macros to validate and streamline reporting.
Sales Associate at BillSave (Utility Sales)
July 1, 2025 - October 25, 2025
Met or Exceeded weekly sales targets by 10%+ through data-driven prospect segmentation and A/B-tested pitch strategies.
Product Technician at Johnson & Johnson Vision Care (JnJ)
May 1, 2024 - October 25, 2025
Applied Statistical Process Control (SPC) to high-volume production lines generating 300K+ contact lenses per shift, cutting downtime by 12%. Partnered with cross-functional teams on defect investigations, improving product yield by 7% and maintaining regulatory standards. Built interactive dashboards in Excel that streamlined KPI tracking, cutting audit readiness time by 30% and supporting operator training on quality control practices.
Data Analyst at Directorate of Industrial Training (DIT)
July 1, 2022 - October 25, 2025
Automated weekly KPI reporting with Python and SQL, reducing preparation time by 40% and enabling senior management to make faster, data-informed decisions across 15 regional centres. Designed secure offline-first workflows during COVID-19 that ensured continuity of national certification programs, allowing 10,000+ candidates to complete exams virtually. Increased data accuracy by 35% by introducing standardised ETL processes and Excel macros to validate and streamline reporting.
Sales Associate at BillSave (Utility Sales)
July 1, 2025 - October 25, 2025
Met or Exceeded weekly sales targets by 10%+ through data-driven prospect segmentation and A/B-tested pitch strategies.
Product Technician at Johnson & Johnson Vision Care (JnJ)
May 1, 2024 - October 25, 2025
Applied Statistical Process Control (SPC) to high-volume production lines generating 300K+ contact lenses per shift, cutting downtime by 12%. Partnered with cross-functional teams on defect investigations, improving product yield by 7% and maintaining regulatory standards. Built interactive dashboards in Excel that streamlined KPI tracking, cutting audit readiness time by 30% and supporting operator training on quality control practices.
Data Analyst at Directorate of Industrial Training (DIT)
December 1, 2019 - July 1, 2022
Automated weekly KPI reporting for 15 regional centers using Python and SQL, achieving a 40% reduction in preparation time and strengthening management's data-driven decision-making. Spearheaded cross-functional offline-first data workflows during the COVID-19 lockdown to ensure the continuity of national exams for over 10,000 candidates. Trained and mentored new data entrants and over 20 colleagues on new digital tools and standardized ETL protocols, resulting in increased data accuracy across the institution.
Technical Support Agent at Virgin Media (VM) Ireland
August 1, 2025 - Present
Through structured questioning and VM diagnostic tools, improved customer confidence and loyalty by resolving most cases during the first interaction; maintained strong KPI scores by shortening investigation and resolution cycles; contributed to VM expansion in the Irish market via collaboration tools and knowledge sharing, including consistent fibre-upgrade sales.
Product Technician at Johnson & Johnson Vision Care (JnJ)
November 1, 2022 - May 1, 2024
Applied Statistical Process Control (SPC) to high-volume production lines generating 300K+ contact lenses per shift, cutting downtime by 12%. Collaborated with cross-functional teams to resolve equipment breakdowns and investigate process anomalies, resulting in 7% more peak yield shifts. Participated in knowledge transfer by training new product technicians on the latest generation of semi-autonomous lines, utilizing interactive dashboards to streamline knowledge transfer on quality control practices.

Education

MSc in Artificial Intelligence & Machine Learning at University of Limerick, Ireland
September 1, 2024 - October 25, 2025
BSc in Chemical Engineering at Kyambogo University, Uganda
September 1, 2015 - December 1, 2019
MSc in Artificial Intelligence & Machine Learning at University of Limerick, Ireland
September 1, 2024 - October 25, 2025
BSc in Chemical Engineering at Kyambogo University, Uganda
September 1, 2015 - December 1, 2019
Master of Science in Artificial Intelligence & Machine Learning at University of Limerick
September 1, 2024 - December 4, 2025
Bachelor of Science in Chemical Engineering at Kyambogo University
September 1, 2015 - December 1, 2019

Qualifications

Microsoft Azure Data Scientist Associate (DP-100)
January 11, 2030 - October 25, 2025
AWS Certified Solutions Architect – Associate
January 11, 2030 - October 25, 2025
Google Data Analytics Professional Certificate
January 11, 2030 - October 25, 2025
Google Project Management Certificate
January 11, 2030 - October 25, 2025
Microsoft Azure Data Scientist Associate (DP-100)
January 11, 2030 - October 25, 2025
AWS Certified Solutions Architect – Associate
January 11, 2030 - October 25, 2025
Google Data Analytics Professional Certificate
January 11, 2030 - October 25, 2025
Google Project Management Certificate
January 11, 2030 - October 25, 2025
Microsoft Azure Data Scientist Associate (DP-100)
January 11, 2030 - December 4, 2025
AWS Certified Solutions Architect – Associate
January 11, 2030 - December 4, 2025
Google Data Analytics Professional Certificate
January 11, 2030 - December 4, 2025
Google Project Management Certificate
January 11, 2030 - December 4, 2025

Industry Experience

Manufacturing, Healthcare, Education, Software & Internet, Professional Services, Telecommunications, Government
    paper DQN MSPacman Agents

    Built reinforcement learning agents for Ms. Pac-Man using the OpenAI Gym environment. Started with a baseline Deep Q-Network (DQN) and extended it with Double DQN, Upper Confidence Bound (UCB) exploration, and a dueling architecture. Systematically tuned hyperparameters and replay buffer strategies to stabilise training. The best-performing agent, the agent with UCB plus the dueling architecture achieved the highest episodic scores and outperformed the baseline vanilla DQN baseline. Beyond raw scores the different techniques produced agents with different behaviours, by studying these differences I was able to tune the agents in order to improve performance.

    paper Serverless AI Pipeline for Quality Inspection on AWS

    Designed and deployed a serverless AI pipeline on AWS to automate visual inspection of manufacturing parts. Trained a convolutional neural network in Python to detect surface defects, containerised the model with Docker, and deployed on AWS Lambda with Step Functions for orchestration. Results were logged in DynamoDB and S3 with annotated images, and system performance monitored through CloudWatch. Achieved over 70% classification accuracy and validated deployment on industrial Mini-PC hardware.