I build backend services, AI systems, and data tooling. Most of it has no interface: it runs as an endpoint, a queue worker, or a script somebody runs between test days.
I started on ASU's Formula SAE team and still write the drivetrain group's analysis tooling, which is where the telemetry further down comes from. Four internships since, all backend or AI systems.
That tool reports vehicle speed and differential slip, and refuses to report cornering load. Only the two driven wheels are logged, so any cornering figure derived from them is wrong, and it leaves the number out rather than printing something the team might tune against.
Education
Arizona State University
B.S. Computer Science · Expected May 2028 · Tempe, AZ
Pop Life Photo
A simulated worker log, scripted so one cycle shows every path: a clean delivery, a row another worker had already locked, three backoff attempts, the dead-letter queue, and the reconciliation pass that requeues it.
Sedai
4 of 5 requests routed to haiku-4.5; the turn the user is waiting on stays on opus-5
A simulated request stream showing the routing rule only. It reports no token or latency savings, because those would be benchmarks and none are published.
Sedai
Xceptional Learning
Sun Devil Motorsports, Formula SAE
A statusline for Claude Code, published to npm and installed about a thousand times at its peak. It surfaces live context usage, the rate-limit window, how many agents are running, the model, and the git branch, in one line that has to stay readable at any terminal width.
npm · Node.js · Git
The published statusline rebuilt for this page, stepping through a simulated session. Context climbs through a turn and drops when it compacts.
Formula SAE telemetry tooling: it turns rear wheel-speed and steering logs into drivetrain physics, then collapses the result into discrete launch, braking and wheelspin events the team can act on between test days.
It also refuses to compute lateral g. Only the two driven wheels are logged, so the left-right split is wheelspin through the differential, not chassis yaw. Deriving cornering load from it gives numbers above 3 g even after aggressive filtering, which is not possible, so the tool reports what the data supports and stops there.
Python · Pandas · NumPy · SciPy · Matplotlib
Pulls audio from Google Cloud Storage, transcribes it, then runs the transcript through three emotion classifiers and keeps the highest-confidence prediction. Gemini writes the summary. It runs end to end with no manual steps.
The three classifiers disagree by design: they were trained on different label sets, at 28, 11 and 7 emotions. A singleton cache loads all three once at startup, so the cost of a cold start is paid a single time rather than on every analysis.
Python · Transformers · PyTorch · GCS · Gemini
Stage order for one analysis, read from the repository. The three classifiers run one after another, not concurrently. The first pass pays for loading all three models; later passes reuse the cache and skip that stage entirely. Relative shape only, not measured timings.
An offline iOS app that scans Pokémon cards with the Vision framework, fuzzy-matches them against a 4,400-name dictionary, and tracks inventory in SwiftData. No backend at all.
Swift · SwiftUI · Vision · SwiftData
More on github.com/JeremyEltho.
I'm looking for a 2027 software engineering internship in the Bay Area. Email is the fastest way to reach me.