Hi

I'm

Siddhant Rajhans.

I'm a Machine Learning Engineer specializing in production AI systems, agentic architectures, and multimodal RAG. My passion is building intelligent systems that process 400M+ records/month and push the boundaries of what's possible with frontier models.

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Siddhant Rajhans

Explore My Latest Projects

CortexLab Architecture

CortexLab: Brain Encoding Toolkit

Multimodal fMRI brain encoding toolkit built on Meta's TRIBE v2. Streaming inference, ROI attention maps, modality attribution, brain-alignment benchmarking (RSA, CKA, Procrustes), and cognitive load scoring.

PyTorchLLaMA 3.2fMRINeuroscienceInterpretability
DreamStudio Architecture

DreamStudio: AI Cinematic Story Director

AI-powered cinematic story director. Speak naturally, point your camera, and watch scenes materialize as images, video, and music in real-time. Full-stack app with web, mobile, and Python backend.

Gemini LiveImagen 4Veo 3.1Lyria 2FlutterPython
Data Pipeline Architecture

Messaging-Based Data Pipeline

End-to-end streaming pipeline processing 400M+ daily events with 65s latency (p95). Kappa architecture with event-time processing, watermarking, and fault tolerance sustaining 5K events/sec throughput (12K peak).

KafkaPySparkDockerAirflowHiveNiFi
Multimodal RAG Architecture

Multimodal RAG for Scientific Literature

Textual + multimodal RAG system for multi-turn conversational queries over 500K+ papers. Agent evaluation metrics for grounding across 2.3M figures, 890K tables, 410K equations. 94% recall at sub-100ms latency.

LangGraphSciBERTCLIPTAPASFAISSOCR
Bike Lane Sentinel Architecture

Bike Lane Sentinel

Computer vision system that monitors illegal vehicle encroachment into NYC bike lanes and automatically alerts NYC DOT. Real-time detection with interactive dashboard and evidence capture.

Computer VisionTypeScriptReactNode.jsReal-time

Built Production Systems & Shipped Real Products.

2023 - 2024

Machine Learning Engineer

Stealth Health-tech Company (NDA)

  • Achieved <65s p95 latency processing 400M+ healthcare records/month via scalable ML pipelines on AWS with Airflow and Docker.
  • Improved clinical data retrieval accuracy by 30% applying advanced NLP and multimodal models to unstructured medical data.
  • Increased user engagement by 25% through agentic AI systems enabling adaptive, personalized interactions.
AWSAirflowDockerNLPAgentic AI
2023

Software Development Engineer Intern

Stealth Health-tech Company (NDA)

  • Boosted platform responsiveness by 35% and user engagement by 20% integrating ML models into interactive healthcare platforms.
  • Reduced average request latency by 40% and increased throughput 3x optimizing backend services, APIs, and data pipelines.
ML IntegrationAPIsBackend Optimization

Technologies and Tools I Work With

Core ML & Deep Learning

PyTorchTensorFlowScikit-learnXGBoostLightGBMTransformersHugging Face

LLM, Agents & Evaluation

LangGraphRAGAgentic OrchestrationPrompt EngineeringEvaluation FrameworksBenchmark DesignGuardrails

Data & Infrastructure

PythonC/C++CUDASQLApache SparkKafkaRedisFAISSPostgres/PgvectorS3OpenSearch

MLOps & Cloud

AWSSageMakerEKSEMRDockerAirflowMLflowW&BGrafana

Research Publications

IEEE ICCE 2025

CNN-Based Detection Mechanism for Deepfake Image

A Mishra, S Rajhans, BB Gupta, KT Chui

Springer, ICRTC 2025

The Evolving Landscape of Cloud Computing: AI Integration, Threats, Challenges and Security Concerns

P Singh, S Rajhans

Springer, ICSPN 2023

Machine Learning and AI in Cybersecurity: Insights and Solutions

SP Rajhans Siddhant, Mishra Anupama

Education & Credentials

2025–2026

MS in Machine Learning

Stevens Institute of Technology

Hoboken, NJ
 

B.Tech in Computer Science & Engineering

Swami Rama Himalayan University

Dehradun, India
Training and Fine-tuning LLMs, W&B Machine Learning, Stanford / Coursera Generative AI with Diffusion Models, NVIDIA Cloud Computing Diploma, IBM