Nikhil R. Nigam

Machine Learning Engineer

I build the infrastructure that makes AI reliable. From Sub-second Vector Search to Privacy-First RAG systems, I bridge the gap between research prototypes and production durability.

SYSTEM KERNEL [ONLINE]
Core
Python PyTorch Lightning LangChain TensorFlow
Infra
AWS (EC2/S3/EFS) Docker Milvus Flask Linux
Ops
MLflow W&B Git SQL

Selected Deployments

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2025

Meet-Me: The Digital Twin

An agentic RAG-based personal interface bridging the gap between static resumes and technical deep-dives.

#FastAPI#Qdrant#Groq#Astro#RAG#AgenticWorkflow
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<400ms TTFT (Time To First Token)
2024

Intelligent Model Recommendation

Sub-second recommendation engine analyzing high-dimensional meta-features via Milvus.

#PyTorch#Milvus#RecSys#System Design
<1s latency
2024

Privacy-First OCR Pipeline

Hybrid compliance workflow using local Ollama models and EasyOCR.

#Ollama#Local LLM#Privacy#Computer Vision
100% Local Inference
2023

Generative MRI Restoration

Adapting Stable Diffusion to replace slow, iterative MRI correction with real-time generative inference.

#GenAI#Stable Diffusion#Medical Imaging#Research
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68% Error Reduction
2022

Deep Learning for Wireless CSI Compression

Novel 3D Convolutional Autoencoder handling variable input dimensions for massive MIMO CSI feedback.

#Deep Learning#Wireless Communication#Compression#Research
40% Bandwidth Reduction
2025

Distributed LLM Systems Lab

Production-grade monorepo for distributed large language model systems: federated learning, speculative decoding, split inference, and distributed training.

#PyTorch#Distributed Systems#LLMs#System Design#Research
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82% Draft Alignment
2025

LLM Router: High-Performance Semantic Orchestration

A forensic laboratory for optimizing latency vs semantics in distributed LLM systems with hybrid routing and DPO-based continuous improvement.

#Python#LLMs#FastAPI#System Design#Performance
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<50ms Routing Overhead
# NIKHIL_TWIN_V1.0 [KERNEL: STABLE]
SYSTEM:
Initialization complete. I have indexed Nikhil's project vault and production history. Ready for query.
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