Eric Cheng

Tech Lead for Ramp's Fraud detection platform

• Optimizing IP and MPLS routing protocols (BGP, OSPF, IS-IS, PIM, LDP, RSVP) and Layer 2 protocols (ARP, STP) • Researching tensor and model parallelism for distributed LLM training to reduce network bottlenecks

• Engineered an end to end no-code rules engine, involving a drag and drop UI, an expression compiler/interpreter, and a python code emitter to enable fraud analysts to develop advanced vectorized DSL fraud rules without prior knowledge • Researched streaming processors + parallelization for time travel queries to build a scalable machine learning feature store • Lectured 150+ engineers on LLM powered structured extraction and built an internal tool to optimize prompt parameters

• Part of a small team building fintech products that drive 40% of overall company revenue • Interfacing with Operations and Product team stakeholders to continue to support last year's intern project • Upgraded entire API platform for handling of PCI-DSS sensitive info and enabled new processors (Marqeta, Adyen, Stripe) • Owned an UX and code for an endpoint used to provide thousands of customers with new virtual credit cards • Scribed architecture discussions and groomed tickets on a backend system handling >10 billion USD of TPV per month

• Responsible for driving product thinking and managing a team of 15 developers and designers to deliver an original product supporting a nonprofit’s needs. Implementing AGILE methodology and in charge of all stakeholder communications • Working with the nonprofit Boundless Brilliance to develop a platform to scale their education workshop offerings

Worked with the Ron Finley Project, a nonprofit focused on transforming food deserts, to develop a project to improve their operational efficiency. Created a volunteer management platform with UX flows for creating/managing events, signing up as a volunteer, and managing user data.

Contract with Wintec Industries to implement AI-powered QA solution in manufacturing plants behind $75 million in sales Created a Computer Vision project to identify faulty microchips, built on a tech stack of Python, Tensorflow, and OpenCV

• Part of a team driving 1.5 billion in revenue per quarter in the B2B fintech space • Spearheaded a project aimed at improving payment operational efficiency and saving developer bandwidth • Developed an overhaul of 40+ tools with documentation generated by a modular, intelligent agent system that served instructions + sample format and automatically updated end user UX based on backend code changes • Achieved a 3X increase in NPS scores to 75 based on end user surveys

Performed database migration, developed internal payroll tools, and developed external website tools (External tools that I worked on can be found here: https://www.aatbio.com/fluorescence-excitation-emission-spectrum-graph-viewer/ )

Major GPA: 4.0 GPA: 3.9 Computer Science and Applied Math double major