rmatif

Mobile Developer

https://talent.gravityer.com/rmatif

Member since June 28, 2026

Key Strengths

Demonstrated strong interest and practical experience in mobile-adjacent technologies through personal projects.
Proficiency in C++ and Dart, which are highly relevant for mobile development, especially for performance-critical applications and cross-platform frameworks like Flutter.
Experience with LLM inference on device (llama.cpp, Local-Diffusion) indicates advanced problem-solving skills and an understanding of optimizing complex algorithms for constrained environments.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and highly technical, focusing on cutting-edge areas like on-device AI/ML. This indicates a strong drive for innovation and self-directed learning. However, the lack of team-based projects or professional experience makes it difficult to assess collaboration and adaptability within a structured team environment. The projects align well with a technically challenging and innovative culture.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

civitai-comfy-nodes

June 13, 2026 – Present

ComfyUI custom node pack exposing Civitai Orchestration recipe endpoints as generated nodes

View Project

GGUF-tensor-rules-gen

January 12, 2026 – Present

GGUF Tensor Type Rules Generator

View Project

Local-Diffusion

November 17, 2024 – July 21, 2025

Run SD1.x/2.x/3.x, SDXL, and FLUX.1 on your phone device

View Project

llama.cpp

March 10, 2023 – Present

LLM inference in C/C++

View Project

Key Strengths

Demonstrated strong interest and practical experience in mobile-adjacent technologies through personal projects.
Proficiency in C++ and Dart, which are highly relevant for mobile development, especially for performance-critical applications and cross-platform frameworks like Flutter.
Experience with LLM inference on device (llama.cpp, Local-Diffusion) indicates advanced problem-solving skills and an understanding of optimizing complex algorithms for constrained environments.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

rmatif

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit