AI Researcher & Systems Software Engineer building first-principles deep learning architectures, intelligent AI proxies, multimodal systems, and high-concurrency microservices. Experienced in bridging theoretical AI research (NeurIPS evaluation frameworks, continual learning, dual-system neural networks) with battle-tested production software engineering (C++, Python, PyTorch, Node.js, Redis, Supabase, Docker).
- 🧪 AI Scientist / Research Engineer — Deep Learning Architectures, Continual Learning, Dual-System Neural Nets, Transformer & CNN Math from Scratch.
- 📊 Data Scientist / Analytics Engineer — Predictive Modeling, Statistical Inference, Exploratory Data Analysis, SQL Pipelines.
- ⚡ AI Engineer / GenAI Specialist — LLM Infrastructure & Proxies, RAG, Agentic AI Workflows, Natural Language Voice Processing.
- 💻 Software Development Engineer (SDE / Backend / Mobile) — Clean Architecture, High-Throughput C++/Python/Node Services, Redis Caching, Cross-Platform Mobile Apps.
🧠 AI Scientist
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📈 Data Scientist
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⚡ AI Engineer
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💻 Software Development Engineer (SDE)
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| Project & Role Focus | Authentic Technical Highlights | Links & Tech Stack |
|---|---|---|
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🧠 ANTARA - NeurIPS Evaluation Suite Target: AI Scientist / Deep Learning Researcher |
• Mathematically hardened benchmark suite evaluating dual-system neural architectures (System 1: OGD, System 2: RGW). • Prevents catastrophic forgetting on 10-task CIFAR-100 partitions without raw data rehearsal. • Multi-node distributed cluster evaluation with live Weights & Biases (W&B) telemetry tracking BWT, FWT, and step latency. |
[GitHub Repo]PyTorch PythonCUDA W&BDocker
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🤖 GPT from First Principles (Pure NumPy) Target: AI Scientist / AI Engineer / SDE |
• Complete from-scratch implementation of Generative Pre-trained Transformer (GPT) using strictly NumPy. • Full forward & backward propagation derived from scratch without deep learning frameworks. • Built multi-head attention, layer norm, positional embeddings, causal masking, and Adam optimization math. |
[GitHub Repo]Python NumPyLinear AlgebraBackprop
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👁️ NumPy CNN Engine from Scratch Target: AI Scientist / Computer Vision Engineer |
• Pure NumPy Convolutional Neural Network engine with zero high-level framework dependencies. • Manual backprop derivation for Conv2D, MaxPool, AvgPool, and BatchNorm2D. • Implemented 8 activations (GELU, Swish), 7 losses (Focal, Huber), and 6 optimizers (Adam, Nadam, SGD momentum). |
[GitHub Repo]Python NumPyMath & BackpropOptimization
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⚡ A.R.C. Intelligent Performance Proxy Target: AI Engineer / SDE Backend Developer |
• Express.js command center and AI proxy powered by Claude 3.5 Sonnet. • Multi-endpoint pipeline handling natural language voice log parsing (Multer `.m4a`), macro extraction, and daily strategy synthesis. • In-memory Redis store managing |
[GitHub Repo]Node.js ExpressClaude API RedisSupabase
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📱 Skyforce HR & OnSpace Mobile Suite Target: SDE / Cross-Platform Mobile Engineer |
• Enterprise cross-platform mobile application built with React Native, Expo, and TypeScript. • Seamless backend integration with Supabase for authentication, real-time data sync, and relational queries. • Native Android/iOS deployment pipelines with smooth Lottie micro-animations and calendar workflows. |
[GitHub Repo]React Native ExpoTypeScript Supabase
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#!/usr/bin/env python3
"""
Suryaansh Prithvijit Singh - Verified Engineer Profile
Target Roles: AI Scientist | Data Scientist | AI Engineer | SDE
"""
class SuryaanshProfile:
def __init__(self):
self.name = "Suryaansh Prithvijit Singh"
self.github = "https://github.com/Ultron09"
self.email = "connect.singha@gmail.com"
self.linkedin = "https://www.linkedin.com/in/suryaansh-prithvijit-singh/"
self.active_research = [
"ANTARA: Continual Learning & Dual System OGD/RGW Architectures (NeurIPS)",
"From-Scratch Autoregressive Transformers (NumPy-GPT)",
"Pure NumPy CNN Layer & Backprop Mathematics Engine"
]
self.production_systems = [
"A.R.C.: Express & Claude 3.5 Performance Proxy with Redis Sorted Sets",
"Skyforce HR: React Native & Expo Cross-Platform Agentic Mobile Suite"
]
def status(self) -> dict:
return {
"hire_status": "OPEN_TO_ELITE_ROLES 🚀",
"primary_focus": ["AI Scientist", "Data Scientist", "AI Engineer", "Software Engineer (SDE)"],
"availability": "Immediate / Global Remote & Relocation"
}
if __name__ == "__main__":
dev = SuryaanshProfile()
print(f"⚡ {dev.name} [{dev.github}] is active.")
print(f"🎯 Status: {dev.status()['hire_status']}")Actively interviewing for AI Scientist, Data Scientist, AI Engineer, and Software Development Engineer (SDE) roles.
⚡ Expected Response Time: Within 12-24 Hours
