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Onani Jongella

@onanijongella

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Data Science and AI Engineer building TinyML bird monitoring on ESP32-S3 with Edge Impulse.

Tanzania

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What I'm looking for

I'm interested in developing data-driven and AI solutions for real-world challenges.

At Mbeya University of Science and Technology (MUST), I applied AI, machine learning, IoT, and edge computing to practical technical problems during field practical training. I also explored deploying AI models on resource-constrained edge devices.

At Camelabs (NileAGI), I implemented deep learning models for computer vision, built and fine-tuned large language models, and worked with GANs for synthetic image generation. I developed ML pipelines and created interactive dashboards for interpreting model results.

For my final-year engineering project, I designed an IoT and TinyML-based smart bird monitoring system for rice crop protection. I implemented real-time inference on ESP32-S3 hardware using Edge Impulse and evaluated model performance and resource requirements for edge deployment.

Experience

Work history, roles, and key accomplishments

AI, IoT and Edge Computing

Mbeya University of Science and Technology

Jul 2025 - Oct 2025 (3 months)

Applied AI, IoT, and edge computing concepts to practical technical problems, including data collection, preprocessing, model development, and evaluation. Explored deployment of AI models on resource-constrained edge devices.

AI Machine Learning IoT Edge Computing data preprocessing Model Development Model Evaluation Embedded Systems

Deep Learning Engineer

Camelabs (NileAGI)

Jul 2024 - Sep 2024 (2 months)

Implemented deep learning models using TensorFlow and PyTorch for computer vision tasks, including image classification and object detection. Built and fine-tuned LLMs for text generation and developed end-to-end ML pipelines.

Deep Learning TensorFlow PyTorch Computer Vision Image Classification Object Detection LLM Gan ML Pipelines Hyperparameter Tuning Data Augmentation Feature Extraction Dashboarding

Machine Learning Analyst

Camelabs (NileAGI)

Jul 2023 - Sep 2023 (2 months)

Performed data analysis, cleaning, and preprocessing for small and medium-sized datasets using Python and data science libraries. Trained traditional machine learning models and developed a fraud detection mini-project.