Technical Skills

Languages: JavaScript, TypeScript, SQL, Python, Java
Backend: Node.js, Express, REST APIs, OAuth 2.0, PostgreSQL, Redis, NPM, WebSockets, Microservices
Cloud & Serverless: AWS (RDS, S3, Lambda, API Gateway, Kinesis, CloudWatch Logs & Alarms), Docker
Frontend: React.js, React Native, Gatsby, Material UI, D3.js
DevOps & Tooling: Git, Buddy CI, Linux, Retool, Metabase, Figma

Experience

Smartcar — Software Engineer II

Dec 2021 - May 2025 Mountain View, CA (Remote)

• Owned development of dozens of full-stack API features connecting 35+ car brands, enabling developers to interact with connected vehicles through a unified, consent-based interface
• Built a sliding window rate-limiting system to prevent traffic bursts and reduce upstream errors, improving API stability and reliability for developers
• Engineered real-time ingestion pipelines for streaming vehicle data, integrating Firehose/Kinesis data into analytics tools for observability
• Developed Backend-for-Frontend service to support a redesigned Developer Dashboard, enabling data-driven UX features and customer usage analytics, boosting dashboard engagement by 30%
• Regularly contributed to cross-functional project planning, writing and scoping tickets, and mentoring junior teammates on debugging, automated testing (Selenium, Jest, Mocha), monitoring, and log instrumentation
• Promoted twice in less than 3 years - setting a company record

USC Information Sciences Institute (ISI), AI Division – Summer Research Intern

May 2018 – Aug 2019 Los Angeles, CA

• Collaborated with researchers at a global neuroimaging consortium to design a structured knowledge base with semantic search capabilities via SPARQL — enabling neuroscience teams worldwide to query and explore interconnected research data
• Designed data transformation logic for T2WML, a tool for mapping tabular data to Wikidata, enabling ingestion of large CSV datasets (e.g. 2M+ rows) into structured knowledge graphs

Deep Brain Neurotech Lab, University of Maryland — Research Intern & Peer Mentor

Aug 2017 – Jan 2019 College Park, MD

• Built and simulated biologically realistic neuronal networks in NEURON using Python, modelling biochemical neural activity under an FDA M-CERSI grant to support non-invasive treatments for neurodegenerative disorders (e.g., TMS, EMS)
• Partnered with clinical researchers to identify and resolve data inconsistencies in 3D neuroimaging outputs, refining simulation results for accuracy and reliability
• Trained and mentored 40+ students, facilitating peer learning and tool usage

Additional Experience & Leadership

• Grace Hopper Conference Scholar – 2018
• Girls Who Code Tutor, University of Maryland

Education

University of Maryland, College Park — B.S. in Computer Science

2017 – 2021