Computer Scientist
Technical Skills: Python, Git, React Native, Bash, Next.js
Education
-
BS/MS, Computer Science |
Georgia Institute of Technology (May 2025) |
Work Experience
ML Operations Engineer @ Linkt AI (December 2023 - Present)
- Developed a video-streaming web application, used Next.js, Roboflow and ONNX to run computer vision models on the client side.
- Designed REST and WebSocket API’s on the backend, utilized FastAPI and Tornado to handle real-time requests to image to image
matching algorithms on the backend.
- Fine-tuned DistilBERT to 98% accuracy on clients dataset, replacing a GPT-3 powered classifier, cutting inference cost by 200%.
ML Engineer Intern @ Dekco AI (June 2023 - September 2023)
- Deployed a transformer-based autocomplete engine using Python, Docker and AWS SageMaker, to speed up composition of medical reports for clinicians by 60%.
- Fine-tuned 200-million parameter LM’s with CUDA, using K-Bit-Training and qLoRA to minimize compute overhead by 98%.
- Designed a text parser to ethically extract relevant data from medical reports, creating the training corpus for an intelligent agent.
- Developed an AutoML frontend with StreamLit and FastAPI to receive realtime feedback from domain experts and foster domain-specific model alignment.
Projects
Applying DALL-E 3 to Novel Illustration
- Deployed a web app using Python, StreamLit Cloud and OpenAI, enabling readers to create AI-generated illustrations for novels.
- Won 1st place at the AI ATL hackathon for Best Use of StreamLit, out of 70 competing teams.
Predictive Analytics Dashboard for Soccer Players
- Conducted data analysis of the SoccerTrack dataset, developing player trajectory plots, characteristic area analyses + visualizations
- Used the time series data to train an LSTM neural network to predict the future positions of soccer players and the ball.