Kerrn Reehal

Software Engineer II — backend, systems, and product

About

I’m a Software Engineer II at StubHub in New York, working on listing systems, event-driven product flows, and experimentation. Before that I interned at Amazon (Alexa inference) and Datadog (DDSQL). I studied EECS at UC Berkeley.

I like systems work that shows up in a product: architectures you can operate, tests that move a metric, tools the team can actually ship.

Experience

  1. StubHub

    Software Engineer II

    – Present

    Software Engineer I

    – December 2025

    • Re-architected the alternative listing classification engine and data model, decomposing 3,000+ lines of monolithic business logic into a modular, scalable architecture with rich telemetry for diagnosing listing eligibility, performance bottlenecks, and bugs.
    • Helped modernize the automatic substitution engine by migrating monolithic, cron-based orchestration to a scalable event-driven architecture that evaluates every listing created on the site, so the product can incorporate new signals and optimize resolution decisions for positive buyer outcomes.
    • Modernized the team’s internal tool suite by migrating IIS-hosted .NET Framework applications to independently deployable .NET Core services with automated CI/CD pipelines.
    • Launched and analyzed 50+ A/B tests, independently driving a 10% reduction in buyer refund rate.
  2. Amazon

    Software Engineer Intern

    – August 2023

    • Alexa Deep Learning Core: low-latency, memory-optimized C++ inference engines for in-cloud and on-device Alexa Speech models, on generic and specialized chips.
    • Integrated the AWS Neuron Runtime into Alexa’s inference engine, enabling inference on Inferentia with a 4× cost reduction vs NVIDIA CUDA at equivalent latency.
    • Used multithreading and load balancing on Inferentia to increase throughput by 2×.
  3. Datadog

    Software Engineer Intern

    – April 2023

    • Optimized DDSQL, a SQL-like language for querying Datadog’s services, using Go.
    • Implemented RBAC for a subset of queries, improving security for customer data.
    • Implemented multithreading to analyze the success rate of millions of queries, improving query language support by 50%, and sped up time-intensive queries by 5×.
  4. UC Berkeley College of Engineering

    Academic Intern

    – August 2022

    • Supported 50+ students weekly as a teaching assistant for CS61C (Computer Architecture), teaching C, virtual memory, and caching in lab and discussion sections.

Education

University of California, Berkeley Berkeley, CA · May 2024
B.S. Electrical Engineering and Computer Science · GPA 3.63

Coursework: Data Structures, Computer Architecture, Operating Systems, Database Systems, Algorithms, Discrete Math and Probability Theory, Computer Security, Artificial Intelligence, Linear Algebra, Differential Equations

Projects

FileSys

February 2024 – March 2024

Secure file sharing system in Go: user authentication, file storage, and sharing, built with cryptographic library functions.

Skills

Go · Python · SQL · C# · C++ · Java
gRPC · AWS (SQS, EventBridge, Lambda) · Postgres · Snowflake · Kubernetes · CI/CD · Git

Interests

Lifting, football, basketball, hiking, swimming. Otherwise: music, or a round of GeoGuessr.