Jayraj Pamnani

M.S. Computer Engineering, New York University

Tandon School of Engineering · Expected May 2026

Jayraj Pamnani
jmp10051@nyu.edu · LinkedIn · GitHub · Resume

About

I am a graduate student in Computer Engineering at New York University's Tandon School of Engineering. My work sits at the intersection of machine learning, deep learning, and systems engineering. I build and optimize AI pipelines—from model training and quantization to deployment—with a focus on making large-scale models practical and efficient.

Prior to NYU, I completed my B.Tech. in Computer Science & Engineering with a specialization in Artificial Intelligence at Parul University (India), where I developed a strong foundation in data structures, pattern recognition, and GPU computing.

Education

M.S. Computer Engineering — New York University, Tandon School of Engineering Expected May 2026

Coursework: High Performance Machine Learning, Machine Learning Operations, Deep Learning, Database Systems, Big Data.

B.Tech. Computer Science & Engineering (AI Specialization) — Parul University, India May 2024

Coursework: Data Structures & Algorithms, Machine Learning, Deep Learning with NLP, Pattern Recognition, Image Processing, GPU Computing, Data Visualization.

Technical Skills

Languages
Python, SQL, C/C++, Java, JavaScript
ML/AI Frameworks
TensorFlow, PyTorch, Matplotlib, Seaborn, Scikit-learn, Neural Networks, Computer Vision, NLP
Data & Cloud
Distributed Systems, AWS, CI/CD, MongoDB, PostgreSQL, Hadoop, Spark, ETL Pipelines, Tableau Dashboards
Tools
Git, Docker, Kubernetes, Jupyter, Gradio, Hugging Face, WandB, n8n, Postman, LangChain

Professional Experience

Software Architect Intern — GBCS Group, Calgary, Canada Nov 2025 – Present
  • Spearheaded the architectural optimization of the group’s software ecosystem, implementing resource efficiency strategies that reduced hosting and maintenance costs by 28%.
  • Reengineered automated CI/CD pipelines and deployment workflows, accelerating release cycles by 40% while ensuring 99.9% system availability.
  • Defined technical standards and architectural roadmaps, guiding development teams in building scalable microservices that reduced technical debt and improved maintainability by 30%.
Teaching Assistant — Machine Learning — New York University, New York, NY Sep 2025 – Dec 2025
  • Guided 50+ graduate students through ML fundamentals, including preprocessing pipelining, supervised/unsupervised learning, Deep Learning, and model optimization techniques.
  • Conducted weekly office hours to debug Python code, explained algorithms, taught ML topics, and assisted with PyTorch implementations.
AI Intern — Swaroop.ai, Ahmedabad, India Mar 2024 – Aug 2024
  • Enhanced TTS model performance by 25% through fine-tuning Coqui TTS across multiple Indian languages.
  • Improved STT accuracy by 18% via domain-specific audio datasets and custom preprocessing.
  • Integrated OpenAI Whisper into production, increasing transcription accuracy on noisy data by 30% and cutting inference latency by 20%.
Data Scientist Intern — Robotskull, Vadodara, India Oct 2023 – Mar 2024
  • Processed 100K+ sales and inventory records; built demand forecasting models achieving 92% prediction accuracy.
  • Automated weekly analytics dashboards, reducing manual reporting time by 70%.
Freelance Software Developer — Vadodara, India Jul 2023 – Sep 2023
  • Engineered a Django-based web app automating data transfer between QuickBooks and KatanaMRP, cutting manual bookkeeping by ~85%.
Teaching Assistant — Parul University, Vadodara, India Oct 2022 – Mar 2023
  • Supported 120+ students in OS concepts and C-based system programming; led weekly lab sessions on Linux programming and multithreading.

Projects

  1. HexDrop (Secure File Transfer)
    Next.js, TypeScript, Prisma, PostgreSQL, AWS, Docker, K8s.
    This secure file-sharing application enables encrypted uploads and key-based downloads using AWS S3 and PostgreSQL.
    The platform operates on a full-stack DevOps pipeline featuring EKS orchestration, automated CI/CD, and scalable cloud infrastructure.
    [code]
  2. EyeConnect: Accessible Video Communication with AI-Powered Vision Assistance
    WebRTC, Supabase, OpenRouter AI, React, TypeScript.
    Accessibility platform connecting blind users with sighted volunteers via real-time video calls and AI vision assistance. Awarded 2nd place at NYU Hacks 2025.
    [code]
  3. Vision Transformer Optimization via Quantization & Efficient Attention
    PyTorch, bitsandbytes, FlashAttention-2, LoRA.
    Optimized ViT-L/16 using 4-bit/8-bit quantization and FlashAttention-2, achieving 4× model size reduction and 40% lower latency with minimal accuracy loss.
    [code]
  4. Model Merging for Large Language Models
    Python, PyTorch, Hugging Face, Google Colab.
    Implemented TIES and SLERP merging techniques to combine Mistral-7B variants with optimized hyperparameters for cross-task generalization.
    [code]
  5. Command Line Helper: Natural Language to Bash via Local LLM
    Converts natural-language instructions into bash commands using a local LLM and RAG-powered context retrieval, with both CLI and web interfaces.
    [code]
  6. Chapter: Secure Library Management System
    Python (Django), Oracle Data Modeler, HTML/CSS/JS, Oracle DB.
    Library management web application with role-based authentication, SQL-injection protection, and an employee dashboard for business metrics.
    [code]

A full list of repositories is available on GitHub.

Selected Certifications