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aditeya08varma/README.md

Hi, I'm Aditeya Varma

Software Engineer working on backend systems, networking, and applied AI.
MS in Computer Science from USC. Based in Los Angeles, CA.

Portfolio LinkedIn Email Resume

Open to full-time Software Engineering roles.


About me

  • ๐ŸŽ“ Completed my M.S. in Computer Science at the University of Southern California in May 2026.
  • ๐Ÿ”ฌ Currently a Graduate Research Assistant at USC's School of Advanced Computing, building a multi-agent LLM code-repair system that is 43% cheaper than an always-on agent team, plus a benchmark that checks whether review agents catch real vulnerabilities.
  • ๐Ÿ› ๏ธ Previously a Software Development Engineer Intern at Amazon, where I cut ETL pipeline latency by 22% and built a testing framework that shrank validation cycles from days to minutes.
  • ๐ŸŒ Active open-source contributor to sageox/ox, a Go CLI used across coding agents. 3 merged pull requests so far.
  • ๐Ÿงฉ My projects range from data analytics and AI agent systems to network protocols, full-stack apps, and a native macOS runtime built at the Mach API level.
  • ๐Ÿ“„ Author of 3 published research papers.

Tech stack

Languages

Python Go TypeScript JavaScript Scala C Swift SQL Bash

Frontend

React Angular Next.js Vite Tailwind CSS D3.js Framer Motion

Backend & Data

FastAPI Django Django REST Framework Pydantic PostgreSQL Redis SQLite DynamoDB Neo4j

AI & ML

LangGraph LangChain PyTorch Hugging Face Claude API Pinecone Pipecat Ragas

Systems & Networking

Linux TCP/IP POSIX Sockets DNS Scapy Open vSwitch Mach APIs Seatbelt Sandboxing

Infra & Streaming

Docker Kubernetes AWS GitHub Actions CI/CD Apache Kafka PyFlink Prometheus Grafana OpenTelemetry

Tools

Git PyTest Claude Code Cursor


Featured projects

๐ŸŽ๏ธ Janus 2.0 (live)

Python | LangGraph | Redis | React 19 | Ragas

  • ๐Ÿง  Agentic RAG system that reasons over FIA technical regulations, with a metadata-filtered retrieval pipeline.
  • ๐Ÿ“Š Reached a 90% Answer Relevancy score on a 20-query evaluation benchmark.
  • ๐Ÿ’พ Thread-isolated session memory across users using LangGraph and a Redis persistence layer.

Swift | C | launchd | Mach APIs | OpenTelemetry

  • โšก Native macOS process isolation runtime with a 55.4 ms cold spawn (2.3x faster than Colima).
  • ๐Ÿชถ 2.9 MB idle footprint, 160x smaller than Docker.
  • ๐Ÿ“ก Telemetry daemon that polls Mach APIs and exports traces over OTLP/HTTP.

Python | POSIX Sockets | Scapy | PyTest

  • ๐Ÿ”Œ Multi-threaded TCP proxy and DNS resolver built directly on raw POSIX sockets.
  • ๐Ÿš€ Repeat lookups drop from 45 ms+ to under 1 ms using a thread-safe LRU/TTL cache.
  • ๐Ÿงช Fault-injection test suite that simulates socket exhaustion and malformed headers.

๐ŸŽฅ Voyager

Kafka | PyFlink | Redis | Python

  • ๐Ÿ“น Real-time multi-camera video pipeline on a 6-partition Kafka topic, targeting under 50 ms per frame.
  • ๐Ÿงฎ Perceptual embedding cache with a 75%+ hit rate, cutting redundant neural network inference.

More projects are on my portfolio.


Publications


Reach out if you want to talk about systems programming, distributed infrastructure, or anything you're building.

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  1. Janus Janus Public

    AI-powered F1 technical regulation assistant: LangGraph agent with Pinecone RAG over FIA regulations, Redis session memory, and a streaming React 19 frontend.

    Python

  2. darwin-server-runtime darwin-server-runtime Public

    Native Darwin process isolation runtime for macOS. Seatbelt sandboxing, launchd-managed daemon, and Mach-level telemetry, built to avoid Docker's Linux VM overhead on Apple Silicon.

    Swift

  3. sageox/ox sageox/ox Public

    The hivemind for AI coding agents โ€” persistent team context recorded once and recalled across agents, machines, and teammates.

    Go 63 20

  4. voyager voyager Public

    Real-time video frame processing pipeline with AI inference caching: Kafka, PyFlink, Redis, and MobileNetV2 embeddings, instrumented with Prometheus/Grafana.

    Python

  5. nba-lineup-explorer nba-lineup-explorer Public

    NBA lineup analytics over real 2024-25 play-by-play data: Django/Postgres backend, Angular frontend.

    Python

  6. readcoach readcoach Public

    Live voice AI reading tutor for grades 1-3 - built for the Nerdy AI Hackathon

    Python