Work Experience
Amazon Web Services
Software Development Engineer II, AWS AI (April 2024 - Present) | Seattle, WA
- Specialized in maintaining, enhancing, and improving Amazon Transcribe, AWS Bedrock Data Automation and Amazon Translate within the AWS Bedrock Generative AI Services organization by leveraging cutting-edge AWS AI/ML models and technologies
- Developed and collaborated on large-scale, advanced automatic speech recognition (ASR) models, significantly enhancing speech-to-text capabilities for up to 30% faster and 2x more accurate transcription services for multi-language use-cases
- Designed, prototyped and now building a new service architecture to completely revamp audio and video tasks with Agentic AI via Bedrock Data Automation to enhance traditional and Generative AI (GenAI) workflows
- Serve as tech lead for AWS Translate, supporting custom feature requests, security mitigations, and continuous service enhancements
- Led the integration of automatic speech recognition (ASR) and speaker diarization models, designing and implementing a new architecture from scratch, for Bedrock Data Automation
- Singlehandely deployed and rolled out our new language identification models in multi language identification transcription workflows
- Led a 3-person team to expand Custom Language Models (CLMs), facilitating the integration of domain-specific knowledge to enhance and produce context-aware transcriptions
- Led the launch of our newest generation of language identification models by implementing new testing suites, testing 100+ cases and ensuring accurate transcription for our customers
- Collaborated with over 30 enterprise customers to architect bespoke solutions, deliver feature requests, and resolve engineering and model-related issues across Amazon Transcribe and Amazon Translate
- Innovated and devised novel strategies to tackle complex ASR technology challenges, with a focus on improving accuracy by up to 50% across various locales and dialects from more than 100 languages
- Optimized deployment and hosting of models on AWS SageMaker, creating an efficient and scalable model serving pipeline
- Improved and optimized scalable pipelines on AWS infrastructure, ensuring high availability and low latency for translation services
- Tech stack: Java (Back-end), Python (Back-end), PyTorch, TensorFlow & AWS AI/ML tools suite
Software Development Engineer I, AWS Lambda (August 2022 - March 2024) | Seattle, WA
- Contributed to a diverse portfolio of products in the AWS Lambda organization as part of the AWS Elastic Beanstalk & App Runner team, collaborating across 5+ teams, blending various research methodologies for internal, open-source, and customer-driven projects
- Led the cross-team integration of AWS WAF into Copilot CLI (Go) for App Runner, ensuring secure apps for thousands of AWS users
- Architected and engineered an automated testing suite that simulates every potential user interaction with the App Runner console to ensure a 99.9% up-time, securing stability and scalability within budget constraints
- Took ownership and led the redevelopment of a versatile internal tool, reducing issue resolution time by up to 85% through systematic evaluation and engineering process refinement
- Improved codebase, worked with product managers and designers to fix multiple bugs and remove numerous customer-facing pain-points for App Runner & Elastic Beanstalk console experience, leading to a 18% increase in service adoption using the console
- Improved team-owned product backend infrastructure by migrating to AWS CDK, enabling efficient deployment methodologies
- Played a pivotal role in the launching App Runner into 3 new regions and catalyzing a multi-million dollar revenue increase for AWS
- Employed AWS ecosystem technologies (EC2, CDK, WAF, CloudWatch, S3, DynamoDB, Lambda) to deliver high-quality solutions
- Tech stack: Go (Back-end), Java (Back-end), Python (Back-end), TypeScript, Node.js, JavaScript (Front-end), React.js & AWS tools
Teradata
Software Engineer Intern (July 2021 – September 2021) | San Diego, CA
- Devised and implemented strategies to streamline storage and management of large objects in the TeraCloud system architecture
- Collaborated with TeraCloud team to restructure storage for large objects within and across Teradata database systems, resulting in 50% more efficient & swift computation for stakeholders
- Engineered sophisticated wrapper functions for use across Teradata systems, ensuring enhanced security, efficiency, and scalability
- Enhanced system reliability and scalability, supporting seamless SQL integration and management of large datasets
- Tech stack: C (Back-end), SQL (Queries) & Teradata database system (Database)
Education
Carnegie Mellon University
Master of Science in Computer Science & Mathematics | | Pittsburgh, PA
August 2025 - June 2027
University of California, San Diego
Bachelor of Science in Computer Science & Mathematics | Cum Laude, Latin Honors | San Diego, CA
September 2019 - June 2022
- Provost Honors, Eleanor Roosevelt College (All Enrolled Quarters)
- Founding & Principal Member, Machine Learning Club at UC San Diego and Member, Data Science Student Society
Certifications
- Machine Learning Specialization by DeepLearning.AI and Stanford Online (2024)
- Deep Learning Specialization by DeepLearning.AI (2024)
- Harvard Business School Credential of Readiness (CORe) (2023)
- Amazon Web Services (AWS) Certified Cloud Practitioner (2020, 2024)
- Amazon Web Services (AWS) Certified AI Practitioner (2024)
Skills
Languages & DevTools: C, Java, Python, Golang, C++, ARM, Java Script, HTML/CSS, JUnit, Puppeteer, MATLAB, R
Libraries & Tools: AWS, GCP, Azure, React JS, Node JS, Numpy, Pandas, PyTorch, TensorFlow, Git, MySQL, MongoDB, IndexedDB
AI/ML Engineering: AWS Managed AI Suite, AWS SageMaker, Bedrock, Fine-tuning, Quantization, Model Inference pipelines