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Software engineer

Aayush Baniya

I build ML systems and do some research.

CS + Math at UT Austin, class of 2028, in Austin. Texas-raised, Nepal-rooted.

$5.5K in hackathons
Aayush Baniya portrait

Selected work

Two products I built and later shut down.

OpenApplierJob-application platform · Retired
aImsgMessaging layer for agents · Retired

Hackathons

Competition projects — all archived.

OnionUSDpOnionDAO · 1st place · 2025$3K
ReproLabAntler × Codex · 2nd place · 2026$2K
VoiceCanvasNepali Leaders of America · 1st place · 2026$1.5K
Agent GraphLaunchD · 2nd place · 2026$500 + residency interview
Change-Aware AuditorAkash Network · 3rd place · 2026$500

Experience

Software Engineer · DeepInvent

Built the agent core for reproducing ML papers from an arXiv ID — 19 model-callable primitives, results decided by measured on-disk evidence rather than the model's grade — and the multi-cloud GPU layer across local, Docker, GCP, and Azure/AKS: one GPU per job, batch-shrink on CUDA OOM, and GCP→Azure failover when capacity runs out.

Jun – Aug 2026

iOS Engineering Intern · MyFutureSelf

One of two engineers taking the app from zero to 5,000+ users and 500+ App Store reviews at 4.7 stars. Owned the SwiftUI launch flows and Firebase sync, and built three StoreKit 2 subscription tiers with server-side receipt validation.

Jul – Oct 2025

Undergraduate Researcher · UT Austin — Learning-Directed OS Lab

Showed that DDS middleware saturation, not CPU, is what breaks a ROS 2 arm: 4,000 msg/s of flooding drove MoveIt on a simulated 7-DOF Panda to 100% execution failure, traced with LTTng and flame graphs. Replaying the same load under cgroups v2 on 32-core CloudLab nodes ruled compute out. Automated the 10-phase CloudLab setup so an experiment runs in minutes instead of hours.

Dec 2024 – May 2026

Independent Researcher · BlueDot Impact — AI Safety Fundamentals

Threw out 8 attention-head findings on a 96-class Time Series Transformer that didn't survive 10,000-resample bootstrap CIs and Benjamini–Hochberg correction. Stress-tested 24 head rankings with Cohen's d under noise, time-warp, and phase-shift — steady on simple tasks (Spearman rho 0.88), falling apart on hard ones (0.48).

Read the write-up

Jan – Feb 2026

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