AI/ML Engineer
Columbia University
Manhattan, NY
03.2024 - 08.2024
- Conducted data analysis, feature engineering, and model selection that identifies the best-performing models for predictive tasks.
- Researched new ML and AI technologies with methods focused on improving performance metrics.
- Utilized deep neural networks to analyze images, videos, and audio signals in order to detect objects or patterns within them.
- Identified potential problems with existing ML and AI systems and proposed solutions for improvement.
- Collaborated with other software engineers to develop end-to-end AI solutions from scratch.
- Integrated pre-trained ML and AI models into web applications using frameworks such as TensorFlow or PyTorch.
- Developed custom APIs for deploying trained models onto cloud services such as AWS or GCP.
- Constructed pipelines for the automation of training, deployment, and evaluation of unsupervised and supervised machine learning
- Cleaned and preprocessed large datasets.
- Created 2D-3D charts and graphs detailing data analysis results.
- Followed industry innovations with emerging trends through scientific articles, conference papers, and postgraduate-level research.
- Conducted Python programming methodologies with scikit-learn packaging.
- Experimented with different regression models such as Lasso, Logistic, and Linear Regression.
- Performed tokenization and punctuation handling with NLPs
- Github project publications and ethical memorandums