# Justin Zhang

> AI Product Eng @ Brain Co. | Ex-Amazon | EECS @ Berkeley

Location: San Francisco, California, United States
Profile: https://flows.cv/justinzhang

## Work Experience
### AI Product Engineer @ Brain Co.
Jan 2026 – Present | San Francisco Bay Area

### Software Development Engineer @ Amazon
Jan 2024 – Jan 2026 | Seattle, WA
● Built a Real-Time Data Ingestion Pipeline using Kinesis Data Streams, Glue Streaming, and
Apache Spark Structured Streaming, reducing Quicksight dashboard latency from daily to
sub-minute updates and enabling real-time analytics for stakeholders
● Took initiative to incorporate GenAI into customer analysis workstreams by developing a new
LLM-based service using Apache Spark and AWS Bedrock (Claude 4.5), reducing manual product
analysis effort by 70%
● Engineered a new personalization pipeline for FireTV including training data preparation, model
training and tuning, and experiment analysis leveraging AWS Personalize, increasing
click-through-rate of selected playlists by 15%
● Implemented a regionalized telemetry service called by FireTV devices using API Gateway and
Lambda with token-based authentication, handling 10,000+ of TPS with sub-100 ms latency,
enabling FireTV Channels internationalization to global markets
● Converted performance-intensive offline SQL join of FireTV item, session, and engagement
events into online real-time data hydration pipeline, enabling real-time features such as video
Continue Watching and reducing peak offline Redshift computational load by 30%
● Re-architected Anomaly Detection service to decouple data retrieval from Redshift, enabling
integration with Athena, Spark, and other data sources, expanding adoption across 5+ teams and
reducing incident response time by up to 80%

### Software Development Intern @ Amazon
Jan 2022 – Jan 2023 | Arlington, Virginia, United States
Designed and implemented an asynchronous AWS Redshift query scheduler for retrieving
information from Amazon Alexa’s Advertising and Engagement Metrics database
Deployed AWS constructs such as Lambda, SQS, Eventbridge, SNS, and DynamoDB using
the AWS CDK and Typescript
Improved precision of scheduled queries from one hour to one minute, and implemented a review
process to increase reliability and safety of new queries

### Summer Intern @ University of Maryland
Jan 2019 – Jan 2019 | College Park, Maryland, United States
Interned under Dr. Dana Dachman-Soled and graduate student Aria Shahverdi
Used Python, Anaconda, and Jupyter Notebook to analyze racial and gender biases in the NYPD Stop and Frisk and the US Census Adult Income datasets; the Pandas library was used for data processing and the Seaborn library was used for data visualization 
Used the Scikit-Learn machine learning library to implement logistic regression and MLP algorithms that attempted to correct biases


## Education
### Electrical Engineering and Computer Science in Computer Science
University of California, Berkeley


## Contact & Social
- LinkedIn: https://linkedin.com/in/jyxzhang

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Source: https://flows.cv/justinzhang
JSON Resume: https://flows.cv/justinzhang/resume.json
Last updated: 2026-03-29