Hindol Roy Choudhury

MLOps Engineer

https://www.opentalent.in/hindol-roy-choudhury-1

MLOps engineer & student researcher

India

Key Strengths

Extensive personal project experience in MLOps, LLMOps, and machine learning.
Demonstrated ability to build end-to-end ML pipelines, including data curation, fine-tuning, and deployment.
Proficiency in Python, Docker, and MLOps orchestration tools (Prefect, Modal) relevant to the MLOps Engineer role.
Experience with LLM inference infrastructure and optimization (e.g., InferSafe, InferSafeV2, V6-optimizer).

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

The-drifter

June 6, 2026 – Present

Galaga-inspired arcade shooter with real-time hand tracking and computer vision controls.

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elemental-research-group.github.io

May 30, 2026 – Present

Website for Elemental Research Lab — a non-profit research group advancing AI safety through mechanistic interpretability.

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Lennard-Jones-Molecular-Dynamics

April 29, 2026 – Present

Lennard-Jones-Molecular-Dynamics — GitHub repository

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InfersafeV2

April 5, 2026 – Present

Production-style LLM serving pipeline with gateway validation, streaming, observability, and live benchmarking on a quantized vLLM backend.

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WorldModelLens

March 24, 2026 – Present

WorldModelLens — GitHub repository

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HydroNet-rainfall

March 7, 2026 – Present

HydroNet-rainfall — GitHub repository

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V6-optimizer

September 14, 2025 – Present

A stability-first optimizer inspired by neural homeostasis and multi-scale memory, extending AdamW for heterogeneous architectures.

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llmforge

June 24, 2025 – July 24, 2025

LLMForge is a modular, automated LLMOps pipeline for Reddit-based data curation and LoRA fine-tuning of TinyLLaMA-1.1B. It features real-world MLOps orchestration with Prefect and Modal, running every 12 hours to ingest, clean, train, and sync models to Hugging Face — fully CI/CD-integrated.

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infersafe

June 18, 2025 – June 19, 2025

InferSafe is a production-grade, self-healing LLM inference infrastructure inspired by companies like Together.ai. Built with modularity, resilience, and scalability in mind

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Loan-approval-prediction-mlops

December 20, 2024 – January 18, 2025

A machine learning solution for automating loan approvals using a RandomForest Classifier. Incorporates MLOps practices for seamless pipeline orchestration, real-time predictions, and efficient deployment.

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Key Strengths

Extensive personal project experience in MLOps, LLMOps, and machine learning.
Demonstrated ability to build end-to-end ML pipelines, including data curation, fine-tuning, and deployment.
Proficiency in Python, Docker, and MLOps orchestration tools (Prefect, Modal) relevant to the MLOps Engineer role.
Experience with LLM inference infrastructure and optimization (e.g., InferSafe, InferSafeV2, V6-optimizer).

Cultural Fit Analysis

The candidate demonstrates a strong inclination towards personal projects, particularly in cutting-edge AI/ML domains like LLMOps and mechanistic interpretability. This indicates a proactive, self-driven individual who is passionate about the field. The diversity of projects, from MLOps pipelines to game development and molecular dynamics, suggests a broad intellectual curiosity. However, the lack of professional experience or team-based projects makes it difficult to fully assess cultural fit in a collaborative, corporate environment.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a strong drive for building complex systems and an understanding of production-grade requirements.

Hindol Roy Choudhury

Key Strengths

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit