Skip to content
View ManikandanBalasubramanian's full-sized avatar
:octocat:
Ahhhmmmmmmmm working on it.
:octocat:
Ahhhmmmmmmmm working on it.

Block or report ManikandanBalasubramanian

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Manikandan

Hi, I'm Manikandan Balasubramanian 👋


Research Engineer @ ZOHO Corp
DevOps DeveloperAI Security EngineerResearch Engineer


LinkedIn GitHub Twitter


🚀 The Journey

I'm a mechanical engineer by training, but it turns out the hardest machines are made of linear algebra. Over the past 9 years, I've tackled three distinct, hard problems in AI each one building the foundation for the next:

🧠 LLM Inference Optimization (2025–Present)

Pushing the boundaries of how efficiently we can serve massive AI models.

  • The Work: Weight quantization (GPTQ, AWQ), KV cache compression, activation-aware methods, and speculative decoding.
  • The Impact: Crafting custom CUDA kernels and leveraging vLLM to deliver identical model quality at a fraction of the compute cost.

🛡️ AI Cybersecurity (2022–2025)

Securing the perimeter with intelligent, model-driven defenses.

  • The Work: Architected ZOHO's core phishing detection engine, evolving from simple URL classifiers to BERT-based analysis and custom multi-head attention models.
  • The Impact: Deployed across messaging, mail, EDR, and browser environments. Built robust PII detection for privacy compliance.

⚙️ ML Infrastructure at Scale (2017–2022)

Building the plumbing that makes enterprise AI possible.

  • The Work: Scaled real-time anomaly detection to handle 10M+ calls/minute and deployed massive 2-30GB production models (ResNet, Seq2Seq).
  • The Impact: Handled Redis sharding, Docker provisioning in hostile environments, and major migrations (Spark 1.5.2 ➔ 2.0, Java 7 ➔ 8). Built REST APIs over legacy JAR inference.

🛠️ Tech Stack

Python C++ PyTorch CUDA vLLM ONNX
Docker Redis Java
---

✍️ Recent Writings

I write about the concepts and technologies that fascinate me mostly deep dives into AI engineering, optimization, and systems.

Check out my latest thoughts in my blog.

📊 Code Stats

LeetCode Stats

"Turned out the hardest machines are made of linear algebra."

Pinned Loading

  1. Archimedes Archimedes Public

    Cuda

  2. blog blog Public

    My name is Manikandan and this is my blog

  3. ManikandanBalasubramanian ManikandanBalasubramanian Public

    1

  4. vllm vllm Public

    Forked from vllm-project/vllm

    A high-throughput and memory-efficient inference and serving engine for LLMs

    Python

  5. vllm-project/llm-compressor vllm-project/llm-compressor Public

    Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM

    Python 3.7k 616

  6. # [Bug]: CompressedTensorsKVCacheMet... # [Bug]: CompressedTensorsKVCacheMethod doesn't set `_scale_float` values — FP8 KV dequantization silently broken on FlashInfer, ROCm AITER, and MLA backends
    1
    ## current environment
    2
    
                  
    3
    ```
    4
    vLLM version: 0.19.0
    5
    PyTorch version: 2.10.0+cu128