Brian Westphal Email & Phone Number

San Jose, CA, US

• Led design of cloud machine learning model inference platform serving millions of IOT devices.
• Reduced company cloud ML inference expenses >50%, by optimizing distributed computation with Ray and profiling model pipelines.
• Maintained >99.999% uptime executing 100’s of millions of cloud ML inference for sensor fusion and computer vision models.
• Reduced development time to release new ML models from months to days establishing an experimentation platform for A/B testing.
• Developed CI/CD systems for managing infrastructure in Kubernetes, ArgoCD and Terraform.
• Orchestrated model evaluation, data labeling, and deployments of quantized models for running on the edge.

San Francisco, California, United States

• Supported ingestion and processing of video for millions of lOT video devices (ex. Dashcams).Tech Stack: Golang, GraphQL, Typescript, React, Terraform, GRPC, Spark, Datadog
• Maintained video processing pipelines for 1M+ IoT video devices and 250k+ videos processed a day.
• Established observability pipelines, documentation, oncall processes to maintain 30+ microservices supporting a $250M+/yr product.
• Developed 4 greenfield camera products to customer releases. Coordinating cross-team integrations across firmware, cloud, and frontend for video visualization of remote devices (ex. Dashcams).
• Worked on embedded systems, creating algorithms to detect harsh driving events based on IMU data.

San Francisco, California, United States

• Contributed to full stack and devops development for advertisement analytics platform tracking billions of events every month.
• Architected anomaly fraud detection system to analyze over 60,000 advertisement click records per minute using Kinesis Streaming Analytics.
• Developed an Elasticsearch ETL pipeline to track billions of events a month utilizing AWS Kinesis, Lambda. Making search in the dashboard easy and rapidly accessible.
• Reduced click-through response time by ~80% (50ms -> 10ms) by introducing asynchronous calls to external services. Bringing customers to the landing pages faster and increasing conversion rates.
• Created unit testing framework for continuous integration with Jenkins for developers to run while checking in pull requests on Github. Speeding up DX workflow and reducing error rates before quality assurance.
• Refined invoicing system which handled over $5 million in transactions per month for the finance team to specify individual events to payout to affiliates. Reducing obligations to pay out fraudulent traffic.

• Founded company that produced $1.5+ million revenue first year by enabling e-commerce shops to automate drop-shipping operations: managing item stock, pricing strategies, and customer service.
• Provisioned cluster of EC2 servers to crawl item pages and provide to the minute updates for price and inventory for over 15,000 listings.
• Utilized Selenium browser to automate daily operations to scale to >25K orders a year.
• Made data labeling platform to provide human in the loop feedback system to manage inventory.Tech Stack: Python, React, GraphQL, Flask, Celery, Selenium Webdriver, Jenkins, Git, RabbitMQ, Celery, EC2, React Relay.

Half Moon Bay, CA

• An agriculture technology startup focused on automating growing operations and harvesting for strawberries. I was employee #2
• Designed and constructed electromechanical systems to handle all aspects of hydroponic plant growth. Including watering systems, creating recipes for nutrient dosing, and cooling.
• Managed daily operations and labor crews.

Anaheim, CA

• Assisted in performing tests and report writing for research and development projects of electro-mechanical chiller and air conditioning units to the specification of airline manufacturers, Boeing and Airbus.
• Utilized Solidworks to produce technical drawings for test schematics, electrical diagrams, and manufacturing to produce parts.
• Completed test for material corrosion for refrigerated parts to the requirements of the Airbus A350.
• Participated in tests for airflow, acoustics, thermodynamic cycles, swing and impact, and control systems.

Master Of Science - Ms, Computer Science - Machine Learning Specialization, 3.88

GPA: 3.88 • Computer Vision • Deep Learning • Reinforcement learning • Knowledge based AI (KBAI) • Artificial Intelligence for Robotics •.

Bachelor'S Degree, Mechanical Engineering, 3.72

Activities and Societies: Polyfounders - Entrepreneurship clubGPA: 3.72

Education record

Activities and Societies: Water Polo, Track and Field, Wrestling