Sainath Ganesh

Software Engineer | Masters CS

San Francisco, Bay Area, CA | sainathganesh1@gmail.com | LinkedIn | GitHub

Summary

Software Engineer with 5+ years of professional and research experience building user-centric, end-to-end applications from conception to production deployment. Winner of 20x hackathons and commended by the Prime Minister of India, Narendra Modi. Earned a Masters in Computer Science with a 4.0 GPA from the University of Illinois, fully funded via research scholarships.

Professional Experience

Software Engineer

May 2023 – Present

Magic Leap – Google Partnership

  • Shipped a productionized XR pipeline for the Google Capture App, integrating with Google backend services to facilitate 3D Gaussian Splats and NeRFs. Launched at 500+ locations around SF and NYC.
  • Built a Gemini-powered calibration tool for 3D content on Google Maps, accelerating QA validation by 10x. Number of scenes calibrated per day increased from ~5 to 50+ per user.
  • Led end-to-end Out of Box Experience for the Magic Leap 2, collaborating cross-functionally with UX, Product and Software teams.

XR Researcher | MS Computer Science

Aug 2022 – Dec 2023

University of Illinois, Urbana-Champaign

  • Optimized upstream video pipelines using Gaze-tracked Foveation, reducing bandwidth by 70% and enabling improved ML inferencing quality on edge and constrained networks.
  • Designed a real-time rendering pipeline for ILLIXR for 3D mesh reconstruction, streaming vertex-colored meshes over websockets via protobuf and optimizing serialization and transfer overheads.
  • Developed network-synchronized XR experiences for the HXRI Lab to study how immersive environments support cognitive and behavioral health outcomes in senior populations.

Software Engineer

Oct 2021 – May 2022

Shell India Markets Pvt. Ltd., Bangalore

  • Built automated data consolidation pipelines for monthly financial reporting, reducing manual processing time by over 90% - from 4 hours down to 10 minutes.
  • Developed report generation tools and dashboards, streamlining financial workflows.
  • Designed discrepancy detection systems to improve reporting accuracy and data integrity.

Education

Master of Computer Science

2022 – 2023

University of Illinois, Urbana-Champaign — GPA: 4.0

B.Tech, Computer Science and Engineering

2017 – 2021

Vellore Institute of Technology, Chennai — Major GPA: 3.7

Technical Skills

Domains: XR, Full-Stack, Agentic & Voice AI, Computer Vision, Cross Platform App Dev

Languages: Typescript (JS), Python, C#, Java, C++, Swift

Full-Stack: React (Native), FastAPI, Firebase, Express, Electron, MERN Stack

XR: Unity, Unreal Engine, ARCore, ARKit

Artificial Intelligence: LangChain, Scikit-learn, OpenCV, NumPy, Pandas, PyTorch, TensorFlow

DevOps: Docker, Google Cloud Platform (GCP), GitHub Actions

Achievements

20x Hackathon Winner

Consistent top finishes in several national and international hackathons.

AI Leadership

2025

Agentic AI Summit - University of California, Berkeley

Speaker at Agentic AI Summit, UC Berkeley after winning LLM Agents hackathon among 1100+ universities and 800+ companies worldwide(Link)

Commended by Prime Minister of India, Narendra Modi

2021

Toycathon 2021 — Ministry of Education, India

Recognized and commended for innovative projects leveraging VR + AI(Link)

NVIDIA Research Grant

2020

COVID AR Hackathon — NVIDIA, Indian Ministry of Commerce and Trade

Research & Projects

Smooth Operator — Multi-Agent Conversational AI

2025

Winner of UC Berkeley LLM Agents Hackathon

Orchestrated a multi-agent system via LangChain and GPT Realtime (via Twilio) that automates conversations with moving companies and negotiates the best quotes, saving users $500–$2,000 per move and reclaiming 3–5 hours of manual effort(Link)

Accelerated Facial Recognition Pipeline

2023

Improved facial encoding search speed by 15x, integrating classical computer-vision filtering via KD-Trees as a preprocessing step to deep convolutional neural networks, reducing compute and improving end-to-end processing by 250%.

Real-Time ADAS for Level-2 Autonomy

2021

Designed and implemented lane-keep assist, pre-collision warning and avoidance, adaptive cruise control and other advanced driver-assistance features, enabling vehicle autonomy with cameras + ML fusion(Link)

Application of Neuroevolution in Autonomous Cars

2020

IVCCPS’20, LNEE Springer

Published research on applying evolutionary algorithms to optimize neural networks for self-driving applications in simulated environments (Paper)