class Au:
def __init__(self):
self.name = "Au Amores"
self.alias = "secureml-au"
self.role = ["AI/ML Engineer", "MLSec Specialist", "Full Stack Developer"]
self.location = "Philippines | GMT+8 | Open to Remote/US Hours"
self.website = "https://au-dev-cs.vercel.app"
self.core_stack = ["PyTorch", "TensorFlow", "OpenCV", "FastAPI", "Flask", "Docker"]
self.focus = ["Computer Vision", "Adversarial ML", "MLOps", "ML Security"]
self.thesis = "Detecting Alcohol Intoxication via Image Processing (CNN+SVM)"
self.metrics = {
"inference_latency" : "<15ms",
"model_accuracy" : "99.8% F1",
"throughput" : "10K events/s",
"onnx_speedup" : "+40%"
}
def current_mission(self):
return "Building hardened AI systems. One model at a time. "
au = Au()
print(au.current_mission())Output →
Building hardened AI systems. One model at a time.
| Deep Learning | Computer Vision | ML Security | Full Stack |
|---|---|---|---|
| CNN / SVM / Hybrid | Real-time YOLO | PhishGuard AI | Next.js / React |
| PyTorch · TensorFlow | OpenCV Pipelines | SQL Injection ML | Flask / FastAPI |
| ONNX Quantization | MobileNetV2 / EfficientNet | NLP Threat Intel | PostgreSQL / MySQL |
| Transfer Learning | Vision Transformers | Adversarial Defense | Docker / Vercel |
| Model Fine-tuning | MediaPipe / Haarcascade | JWT Zero-Trust | Tailwind / Bootstrap |
|
AI-powered facial analysis detecting alcohol intoxication in real-time. Complete on-device CV pipeline with biometric feature extraction deployed on Android. Stack:
|
Enterprise-grade phishing detection using Transformer + ONNX. Flask REST backend + Android frontend with sub-15ms inference latency. Stack:
|
|
Multi-algorithm URL threat intelligence platform classifying malicious web links with <100ms latency. Stack:
|
High-precision NLP spam classifier with minimal false positives across SMS datasets. Stack:
|
|
Secure token-based auth framework with industry-standard bcrypt hashing, session management, and API route protection. Stack:
|
Real-time SQL injection vulnerability auditing tool with Flask API and live web interface for payload testing. Stack:
|
|
Next-gen security awareness platform bridging cryptographic standards with human intuition. Interactive modules on identity management and secure protocols. Stack:
|
|
╔══════════════════════════════════════════════════════════════════════╗
║ TIMELINE: Au Amores // secureml-au ║
╠══════════════════════════════════════════════════════════════════════╣
║ ║
║ ██ 2026 — PRESENT █████████████████████████████ [ACTIVE] ║
║ AI/ML Engineer ║
║ → PhishGuard AI + MLSec pipelines ║
║ → CNN vision systems | <15ms ONNX inference ║
║ → Stack: PyTorch · Flask · Docker · ONNX · OpenCV ║
║ ║
║ ██ 2024 — 2025 ████████████████████████ ║
║ Full Stack Developer ║
║ → Zero-trust JWT auth | 95+ Lighthouse score ║
║ → Stack: Next.js · React · TypeScript · PostgreSQL ║
║ ║
║ ██ 2023 — 2024 █████████████████ ║
║ Software Developer ║
║ → MVPs for Academic & Startup clients ║
║ → Stack: React · JavaScript · Bootstrap · Node.js · Firebase ║
║ ║
║ ██ 2021 — 2023 ████████████ ║
║ Operations & Executive Assistant (US-based Tech Startup) ║
║ → 200+ monthly correspondences | 98% data accuracy ║
║ → -90% wait time via automation ║
║ ║
╚══════════════════════════════════════════════════════════════════════╝
Open to: ML Security Roles · Freelance Contracts · Remote-First · Response <24hrs