About

I am a highly motivated individual with a background in psychology, where my academic journey culminated in a dissertation focused on the intricacies of natural language. During my PhD program, I earned a minor in quantitative sciences and I developed foundational skills for analyzing large datasets. Over the course of graduate studies, I began to delve into the world of natural language models which sparked a deep fascination with the endless possibilities of machine learning models.

Driven by this passion, I decided to broaden my skill set and pursued a degree in computer science. This journey not only honed my programming skills but also allowed me to delve deeper into the realm of machine learning. Now, as a machine learning engineer, I bring a robust foundation in data science, seamlessly combined with my programming expertise, to create innovative solutions and contribute to cutting-edge projects.

Data Analysis 90%

Machine Learning 90%

SQL 85%

MLOps 80%

AWS/Cloud Infrastructure 85%

  • 06/2024 to Present

    Senior Machine Learning Engineer

    Minute Media

  • 11/2022 to 06/2024

    Senior Machine Learning Engineer

    STN Video

  • 10/2021 to 10/2022

    Machine Learning Engineer

    STN Video

  • 09/2018 to 09/2021

    Machine Learning Specialist

    University of British Columbia

  • ................................

    B.Sc. Computer Science

    University of British Columbia

  • ................................

    Ph.D. Psychology, Statistics (Minor)

    University of British Columbia

Technical Skills

Languages

Go Python PHP JavaScript Java SQL R MATLAB

AI/ML & Data Science

SageMaker Bedrock OpenSearch Databricks scikit-learn XGBoost LightGBM TensorFlow PyTorch spaCy Hugging Face OpenCV pandas NumPy

Cloud & Infrastructure

AWS Lambda ECS EC2 Fargate Docker Kubernetes S3 RDS DynamoDB

DevOps & CI/CD

GitHub Jenkins CodePipeline CodeBuild CodeDeploy CodeCommit

Databases & Analytics

MongoDB Redshift Power BI SPSS

Monitoring & Messaging

CloudWatch Azure RabbitMQ SQS

Project Management

Jira Asana Slack

Focus Areas



Applied Machine Learning

Designed and delopyed ML solutions for real-world applications, including human neurological processing, video categorization, brand safety detection and optimized ad serving.



Recommendation Systems

Developed data-driven recommendation systems that fully leverages first and third party data to maximize user engagement in text and video content.




Agentic AI Models

Exploring AI systems that combine large language models with memory, reasoning, and external tools to enable more autonomous and context-aware user interactions.



Cloud-Based ML Infrastructure

Built and deployed scalable machine learning services using cloud infrastructure, containerization, and production-oriented engineering practices with a focus on AWS infrastructure.



NLP & LLM Applications


Researched natural language processing in graduate studies and later applied this expertise to the development, evaluation, and refinement of large language model applications.



Data-Driven Product Development

Collaborated across technical and product teams to translate data insights and machine learning capabilities into impactful user-facing products.