resume · August 2026

Tsolmondorj Natsagdorj

Systems & Research Engineer

I find where an abstraction stops matching reality, then build the test that exposes the gap. My work spans AI evaluation, high-performance networking, scientific ML, protocol correctness, and autonomy, with an emphasis on independent evidence, explicit limitations, and public correction when later validation weakens an earlier result.

Selected technical evidence

roce-preflight systems · networking

Real RDMA execution exposed four defects after 197 unit tests passed; the first attempted fix still failed on-device. Built a Soft-RoCE CI boundary that asserts no simulation fallback, exercises real verbs/sysfs state, and sends perftest traffic.

case study → · source ↗

BRIDGE-bench AI evaluations · security

Audited a real-exploit benchmark and found severe author-injected prompt leakage in 13/24 examples. Downgraded the historical model score to a contaminated upper bound and added sanitizer invariants plus a locked paired remeasurement design.

case study → · revision → · source ↗

active-materials-discovery scientific ML

On a static 18,928-structure perovskite screen, pretrained mean ranking reached DAF 5.15 at a 5% budget; the tested MC-dropout uncertainty signal had Spearman σ↔|error| = −0.47, and overweighting it pushed acquisition below random.

case study → · source ↗

Merged upstream — independent review

MatGL #801 ↗Reusable MC-dropout uncertainty primitive with explicit model-support boundaries.
MatGL #809 ↗Autograd-correct, numerically safe SoftExponential activation.
MLX-LM #1372 ↗Corrected pathological XTC sampling defaults across library, CLI, and server.
Alloy #1105 ↗Self-referential EIP-712 type canonicalization while preserving strict runtime recursion limits.
uutils ↗GNU-compatible date/time semantics across coreutils #12327 and parse_datetime #284/#285/#287.

Current engineering

Suwappu

Build distributed systems, cryptographic protocols, transaction infrastructure, and adversarial-reliability tooling.

suwappu.bot ↗

Aiur current experiment

Autonomy/hardware program reduced to a falsifiable recovery prototype. Current artifacts include design, CAD, simulation, controller logic, and acceptance gates; physical recovery performance remains explicitly unproven until telemetry exists.

source ↗

Formation

George Mason University — studied Economics & Computer Science; left in 2017 to work full-time. Blockchain at Mason — co-founded the student-run, faculty-supported organization in 2016–2017; grew to 90+ members. Full formation →

Selected writing

197 passing tests, four real-hardware bugs · A benchmark can measure its own metadata · Upstream is a different kind of test

Problems I want to work on

I’m most interested in teams where correctness has to survive contact with reality: AI evaluation and inference systems, low-level networking and distributed infrastructure, scientific ML, protocol/cryptographic systems, and autonomy where software eventually has to cross a physical boundary.

layerinfinite@gmail.com · 0xsoftboi.github.io · github.com/0xSoftBoi