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On-Device AI Engineer | Edge Inference | llama.cpp, GGML, C++/JNI, Android | Building at RunAnywhere (YC W26) | Creator of ToolNeuron
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
RunAnywhere (YC W26)
AI Research Engineer
June 13, 2026 – Present
llama.cpp-android
February 23, 2026 – Present
Custom llama.cpp fork with character intelligence engine: control vectors, attention bias, head rescaling, attention temperature, fast weight memory
View ProjectForgeAi
February 9, 2026 – Present
ForgeAI : Your local model workshop, Load. Inspect. Merge. Ship.
View Projectkotlin-starter-example
January 15, 2026 – Present
kotlin-starter-example — GitHub repository
View ProjectAi-Systems-New
January 7, 2026 – Present
On-device AI SDK powering ToolNeuron — LLM chat & tool calling (llama.cpp), Stable Diffusion image generation (QNN/MNN), image processing (upscale, segment, inpaint, depth, style), and TTS. Native C++ + Kotlin JNI. Fork or clone to use in your own app.
View ProjectAi-Core
September 14, 2025 – December 14, 2025
Native C/C++ core for ToolNeuron — JNI + llama.cpp bindings for fast, private, on‐device LLM inference on Android.
View ProjectCultural Fit Analysis
The candidate's project portfolio demonstrates a strong alignment with cutting-edge AI research and development, particularly in the domain of on-device and privacy-focused AI. The target role of 'AI Research Engineer' aligns well with the candidate's demonstrated interests and technical depth in building AI systems from the ground up. The diverse use of technologies (C++, Kotlin, Rust, TypeScript, Svelte) across various AI-related projects indicates adaptability and a broad technical curiosity. However, the candidate's only listed professional experience is current and started recently, which limits the ability to assess long-term cultural fit in a structured corporate environment. The experience level of 0 also suggests this might be an entry into a formal professional role, despite the advanced personal projects.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong drive for innovation and a focus on privacy-first, on-device AI solutions. The breadth of personal projects suggests self-motivation and a proactive approach to learning and development. However, without specific assessment data on communication, logical reasoning, or teamwork, it is difficult to fully assess soft skills and operational fit. The current experience level is 0, which might indicate a lack of professional experience in a team setting, despite the advanced technical skills.