Work Experience
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Latest Experience
Kubernetes
Software Engineering Intern at Two Sigma
Summer 2025
At Two Sigma, I automated Java-based memory allocation for Kubernetes production jobs and implemented comprehensive CI/CD testing pipelines. My work eliminated significant manual interventions, freed engineering resources, and improved data delivery efficiency for memory-intensive pipelines.
Accomplishments:
During my internship at Two Sigma, I focused on automating critical infrastructure operations and improving system reliability. I worked extensively with Java applications running on Kubernetes, implementing memory management solutions that significantly reduced operational overhead.
The automation work involved building robust CI/CD pipelines using Jenkins and integrating with Kafka for real-time monitoring and alerting. This experience gave me deep insights into enterprise-scale DevOps practices and the importance of automation in high-frequency trading environments.
- Automated Java-based memory allocation for Kubernetes production jobs and added comprehensive CI/CD testing, eliminating 8,000 manual interventions/month, freeing one engineer, and expediting data delivery by 30 minutes for OOM-prone pipelines.
During my internship at Two Sigma, I focused on automating critical infrastructure operations and improving system reliability. I worked extensively with Java applications running on Kubernetes, implementing memory management solutions that significantly reduced operational overhead.
The automation work involved building robust CI/CD pipelines using Jenkins and integrating with Kafka for real-time monitoring and alerting. This experience gave me deep insights into enterprise-scale DevOps practices and the importance of automation in high-frequency trading environments.
PyTorch
Hugging Face
ML Intern at Rebellions
Summer 2024
At Rebellions, I optimized machine learning models and accelerated inference performance by 46x using AWS EC2 infrastructure. I analyzed model architectures including Stable Diffusion XL Turbo, and researched CNN and Transformer designs to enhance AI acceleration across hardware and software domains.
Accomplishments:
During my internship at Rebellions, I thoroughly analyzed various machine learning frameworks and model architectures, benefiting from invaluable feedback and mentorship from seasoned industry practitioners. The internship enabled me to enhance my comprehension of AI acceleration in both hardware and software domains. I was able to make a positive impact on the company by conducting research, giving presentations, and implementing text-to-speech model architectures within specific compilation processes.
- Successfully compiled and optimized a custom designed VITS model architecture on Amazon EC2 Inf2 instance, reducing inference time from 4260.83 ms to 90.46 ms, resulting in 46.1 times more throughput.
- Rigorously analyzed the Stable Diffusion XL Turbo model and presented the model architecture, training process, inference process, and benchmarks.
- Researched CNN and Transformer model architectures to improve my understanding, allowing me to better analyze and optimize larger DNNs.
During my internship at Rebellions, I thoroughly analyzed various machine learning frameworks and model architectures, benefiting from invaluable feedback and mentorship from seasoned industry practitioners. The internship enabled me to enhance my comprehension of AI acceleration in both hardware and software domains. I was able to make a positive impact on the company by conducting research, giving presentations, and implementing text-to-speech model architectures within specific compilation processes.
TypeScript
Firebase
Software Developer at Cornell Digital Tech and Innovation
Spring 2024
Developer for CUApts, Cornell's off-campus housing website. I applied Agile development methodologies to improve UI/UX with React and TypeScript, enhanced back-end efficiency using Express.js and Firebase, and implemented features that reduced bug reports by 60% and increased user retention by 45%.
Developer for CUApts, a Cornell Housing Website to help students find off-campus housing.
Accomplishments:
Accomplishments:
- Agile Development, Version Control and Code Reviews: Led Agile development processes, completing weekly sprint tasks and reviewing pull requests, contributing to a 60% reduction in user bug reports.
- Cross-Team Collaboration: Worked with designers to improve UI/UX by making elements more interactive with scroll and hover styling using React and TypeScript, decreasing the site's bounce rate by 15%.
- Improved Back-End Efficiency: Implemented and rewrote RESTful APIs using Express.js to retrieve apartment information more efficiently from Firebase Cloud Firestore, reducing API response time by 14%.
- Improved User Retention: Implemented an email notification system, increasing user return rate by 45%.
- Add price and bedroom attributes to Firestore database script.
- Implemented new design, animations, and functionality for dropdown menus on the website.
- Sorting functionality for Apartments, allowing you to find apartments based on price, rating, number of reviews, and more.
- Designed and Implemented a Review Email System, notifying users when their reviews have been approved to thank users for their contributions to the platform. Designed the email's html and ensured compatibility across email platforms.
- Fixed UI inconsistencies across the website by communicating with the team's designers
- Revamped FAQ Page
- Landlord Redirect Button
- Google Maps Implementation
- Review Modal Redesign
- Apartment Images
- Contact Us Modal
To see more information about my past experience, check out my
page.
