Emmanuel Orimoloye (TOE Tech)
I am a cognitive software engineer focused on mobile systems: on-device AI integration, low-latency edge execution, and local-first distributed architectures. I turn hardware constraints into measurable performance advantages.
I think in the direction of breaking, building, and fixing, following instinct, intuition, and intention before convention.
I like breaking things safely and deliberately, because the same instinct that finds the fault is already telling me how to fix it, which is why I adapt to situations fast and never panic.
01. On-device AI
Executing quantized LLMs (SmolLM2, Gemma, Phi-4) directly on mobile NPU/GPU hardware via LiteRT and native C++ bindings, bypassing cloud latency and API costs.
02. Local-first architecture
Building zero-cloud, sync-engine systems that rely on embedded vector storage, SQLite/mmap disk layers, and event-sourced vector-clock conflict resolution.
03. High-throughput runtimes
Designing ring-buffered memory allocators, thread-per-core proxies, and zero-copy binary streaming protocols using Rust, C++, and Dart FFI.
- 01 · web fundamentals
the basics taught me how the web thinks
Every strong foundation starts quietly. HTML, CSS, and JavaScript taught me how browsers and the network act, and the first frameworks taught me how components and state fit together.
html · css · javascript · framework-first
- 02 · cms platforms
then I learned how content becomes product
I got curious about full sites shipping without code: WordPress, Webflow, Framer, Squarespace, and Wix. They taught me the constraints of one-size-fits-all platforms and why real products outgrow them.
wordpress · webflow · framer · squarespace · wix
- 03 · low-code & no-code
velocity became the obsession
FlutterFlow, Bubble, Notion, and Softr showed me how fast software can ship when the abstraction does the heavy lifting, and where every abstraction hits its ceiling, which is exactly where I eventually went looking.
flutterflow · bubble · notion · softr
- 04 · mobile development
the ceiling I hit was performance
So I went native and cross-platform: Flutter, React Native, Kotlin, Jetpack Compose, and Swift, chasing smooth, dependable experiences on devices with real memory and battery constraints.
flutter · react native · kotlin · jetpack compose · swift
- 05 · full software engineering
now the whole stack, and the intelligence layer
From that foundation I went deep: complex data structures and algorithms, system design, vector databases, and AI engineering. The heavy lifting now happens in Python: shipping models, runtimes, and systems, not just screens.
dsa · system design · vector databases · ai engineering · python
- 06 · software × hardware
finally, bridging the two industries
I currently live at the seam where software meets hardware: on-device AI inference, low-level runtimes, and systems that squeeze measurable performance out of physical constraints.
on-device ai · embedded · c++ / rust bindings
- 07 · ai-augmented engineering
somewhere along the way, AI became a teammate
Somewhere in the middle of all that I started building side-by-side with AI: GitHub Copilot for autocomplete, ChatGPT for fast research, Claude for long-context reasoning, and OpenCode for agentic builds. They moved from novelty to daily practice: I keep the instinct and the review, they handle the boilerplate and the breadth.
github copilot · chatgpt · claude · opencode
I've shipped at hackathons on both sides of the stack: classic web2 builds and on-chain prototypes in web3. Twenty-four-hour pressure is a feature, not a bug: it rewards exactly the kind of adaptive, don't-panic thinking I do best.
Software Engineer
Local ai runtimes, edge systems & low-level performance
Mobile Application Engineer
Cross-platform apps on ios & android
Frontend & CMS Developer
Responsive interfaces, design systems & the modern web
Freelance Developer
Client builds on fiverr, facebook, instagram & x
My work sits at the intersection of application-layer user experience and low-level system performance. Whether architecting offline-first mobile platforms with embedded local servers, building low-latency API proxy shields, or streaming 60 FPS spatial sensor data directly through native device hardware, my focus remains constant: uncompromising stability under memory and network constraints. That arc is deliberate: web fundamentals, CMS, low-code, and mobile each taught me how real users and real constraints behave before I went deep into systems, AI, and hardware.
I regularly write technical deep dives on Medium (@toetech) and Dev.to, documenting benchmarks, memory optimization techniques, and state architecture patterns.
I've also spoken at local community webinars over Google Meet and Zoom, sharing what I've learned about low-latency systems, on-device AI, and the discipline of breaking, building, and fixing software without panicking.
Verification & artifacts
Review my background, technical writeups, and open-source specifications.