Machine Learning Engineer

STANLEY CHIDERA AGWU

+234********** **************@*****.*** https://www.linkedin.com/in/stanlito

https://github.com/stanlitoai Portfolio: https://stanlitoai.github.io/ PROFESSIONAL EXPERIENCE

Machine Learning Engineer

Nabafat.AI, California, United States 2023 – Present

● Architected and Executed CI/CD pipelines using Jenkins, leading to a 40% boost in project deployment reliability and productivity.

● Designed and Deployed a product extraction system using Streamlit and Google's Generative AI, achieving a 40% reduction in document analysis time and a 25% improvement in accuracy.

● Developed ML Pipelines for recommendation systems using collaborative filtering, reducing model training time by 50% and increasing accuracy by 20%.

● Conducted Sentiment Analysis on customer reviews with advanced NLP techniques, providing actionable insights for business strategies.

Computer Vision Engineer

Roc4Tech, France 2022 – 2022

● Created well-documented object detection and Image Segmentation problems with RCNN, Fast-RCNN, Faster-RCNN, YOLO, SSD, Mask-R CNN.

● Leveraged Transfer Learning by extracting weights from ResNet, VGG, and Inception variants to enhance image classification performance.

● Automated Machine Learning Pipelines utilizing TensorFlow, Scikit-learn, and Azure, resulting in a 50% decrease in training time and a 20% improvement in model accuracy. Machine Learning Engineer

ZeroToMastery 2021 – 2022

● Executed Data Collection and Cleaning processes using Pandas and Python, extracting key statistical insights and trends from complex datasets.

● Presented Weekly Progress Reports and findings to stakeholders through compelling visual presentations, ensuring alignment and transparency. Computer Vision Engineer

Sentient LTD 2020 – 2021

● Developed and Integrated an image and plate number recognition system on drones for surveillance monitoring.

● Trained and Deployed deep learning models for fraud detection, enhancing security measures.

● Created and Implemented a plant disease identification system using drones, advancing agricultural monitoring capabilities.

● Engineered Real-time Object Detection and facial recognition across multiple camera feeds, improving surveillance accuracy.

EDUCATION

Enugu State University of Science and Technology

B.Eng in Mechanical and Production Engineering 2017 – 2022 ACHIEVEMENTS

● Developed a customer support assistant and recommendation system(View) 2024

● Created a document description extracting app (Demo) 2024

● Implemented deep learning for disease classification 2023

● Developed real-time computer vision systems using SSD Mobilenet and Faster RNN (View) 2021 PROFESSIONAL CREDENTIALS

● Deep Learning with TensorFlow (View)

● Practical Introduction to Machine Learning with Python (View)

● Complete Machine Learning & Data Science 2022 (View)

● Artificial Intelligence & Machine Learning - Ebook (View) TECHNICAL SKILLS

● Programming Languages: C/C++, Python, Shell, Git, Terminal

● Software Tools: MicroPython, Arduino, Visual Studio Code, PyCharm, Jupyter Notebook

● Machine Learning: Keras, PyTorch, TensorFlow, Ultralytics (YOLO), OpenVINO, OpenCV, SQL

● Computer Vision: Object Detection, Facial Recognition, Image Processing

● MLOps: Jenkins, Docker, Kubernetes, Grafana, GNN, Deep Learning, Logistic Regression, Gradient Boosting Trees

● Cloud Platforms: AWS, Azure

● Data Engineering: Databricks, Spark, Kafka, Airflow, Snowflake

● Frameworks: Flask, FastAPI

LANGUAGE

● Fluent in English

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