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About Me

Hello, I am Joyce. With 4+ years experience in Software Engineering within DevOps, Machine/Deep Learning and Mobile Application fields.

I am interested in sifting and shuffling data to build products that benefit businesses and their customers while implementing secure and private AI tools in most of the projects I build.

I also work with these Languages and Technologies:

  • Python
  • Java
  • Flutter & Dart
  • Html/CSS
  • Bootstrap
  • Jenkins
  • Spark
  • Docker
  • Machine Learning
  • Deep Learning
  • AWS Sagemaker
  • GCP
  • MLOPS
  • SQL
  • Git
  • Tensorflow
  • PyTorch
  • Keras
Resume

What I Do

Machine Learning

I extract, load and transform data.

Use the data to design and train machine learning and deep learning models that I deploy into production on mobile or custom device applications.

I am fascinated by the power of deep learning in technological advancement.

DevOps

I build Docker containers that help remove developers bottlenecks.

I enjoy logging and monitoring software development metrics using Prometheus, Grafana, Elastic Search & MySQL.

I manage Jenkins continuos development and integration platform for software development and validation cycle. I have recently started extending my work to MLOps from POC to Production Deployment and planning out the lifecycle of a machine learning project.

Web and Mobile Development

I design and implement REST APIs to facilitate highly scalable web applications using SQL, DynamoDB, AWS Lambda.

I develop responsive web applications using HTML, CSS, Bootstrap, JavaScript.

I enjoy building mobile applications using Flutter and Dart for Android and iOS devices.

Work Experience

Software Designer | Applications Engineer Hexagon Autonomy & Positioning, Calgary

December 2017 - Present

- Developed a deep learning model that easily identifies satellite signal interference in GPS receivers using CNN, GPUs, Python, Tensorflow and Keras (US Patent-pending)

- Build dashboards with alerting systems for logging and monitoring software development metrics using Prometheus, Grafana, Elastic Search & MySQL. This reduced load failures resolution time by 60%

- Develop, maintain python codes and project documentations

- Participate in code review for other developers within the team

- Investigated and solved 120+ customer support cases related to field deployments of company products in collaboration with team members

Machine Learning/Software Engineering Consultant Upwork | PeoplePerHour, Calgary

January 2020 - Present

- Created a recommendation engine for a real-estate business website using collaborative filtering and a content-based recommendation system

- Predicted business analytical trends for a bike-sharing startup to enable the business to make informed decisions

Software Automation Specialist Stream Systems, Calgary

March - May, 2017

- Performed the complete planning, application development, verification and risks involved in software projects using Selenium and Jenkins

Tracked software bugs and detailed all information regarding findings and resolution techniques in documentation for software designers.

- Produced well-written test scripts for automated testing in Jenkins.

Education

M.Sc. in Computer Science Georgia Institute of Technology

2021-2023

Interactive Intelligent Systems specialization including courses in Human Computer Interation, AI/Machine Learning, Health Informatics, Education Technology and Algorithm Design.

Diploma in Software Engineering NIIT, Takoradi

2015

M.Sc. in Petroleum Geoscience Institute of Petroleum Studies, University of Port Harcourt

2013

B.Tech. in Geology Federal University of Technology, Owerri

Projects

sage_maker
Deploy ML App with AWS S3
An LSTM-based Sentiment Analysis of movie reviews deployed into production on AWS using Sagemaker, EC2 and Lambda Function
know_canada
Know Canada
An app for people to learn more about Canada and prepare for their Canadian citizenship test.
recom_sys
Recommendation Systems
A system to improve the IBM Watson users article recommendation

Blog

churn_rate
Predicting Churn Rate with PySpark
A model for predicting customer churn rate involving data analysis, feature engineering, model training (Random Forest, Logistic Regression and Gradient Boosting Trees) using PySpark on IBM Cloud
raspberry_pi
Federated Learning with Raspberry Pi
Equipment setup for the implementation of federated learning of a recurring neural network on two raspberry pis and virtual workers.
learn_python
Easiest Way To Learn Python
... don't give up