Pranjal Kamboj
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Building intelligent AI systems that power the future. Specializing in LLMs, Multi-Agent Systems, and AI Safety.
Building intelligent AI systems that power the future. Specializing in LLMs, Multi-Agent Systems, and AI Safety.
Building AI systems at the cutting edge of technology
Stealth Startup (AI) · Full-time
Founding ML engineer focused on AI safety and governance. Building protection and policy guard layers for autonomous AI systems through LLM fine-tuning, RLHF, hallucination filtering, and policy-aligned generation.
Stealth AI Startup · Internship
Founding role contributing to R&D in machine learning, AI agents, and multi-agent systems for chip design optimization. Advanced research in generative AI and agent orchestration frameworks.
University of Texas at Arlington
Developed educational AI implementations for Masters-level instruction, including comprehensive multi-agent systems using CrewAI and LangGraph frameworks.
Digitech Software Solutions
Built end-to-end ML pipelines using TensorFlow.js and XGBoost for recommendation systems and predictive analytics. Achieved 95% model accuracy and 40% performance improvement.
2023 — 2025
Computer Science
University of Texas at Arlington
Focus: Machine Learning, Deep Learning, Computer Vision, NLP
2019 — 2023
Computer Science
Guru Gobind Singh Indraprastha University
Focus: Data Structures, Algorithms, Software Engineering
Soumyajit Maity, Pranjal Kamboj, Sneha Maity, Rajat Singh, and Sankhadeep Chatterjee
Accepted for publication in ICICT 2026, London
Cutting-edge AI solutions powered by the latest technologies
Multi-agent workflow using CrewAI for unbiased automotive reviews with 66% faster performance.
Multi-tool LLM agent combining RAG, Wikipedia, Arxiv, Web Search, and Vector DB.
Fine-tuned LLaMA 2 7B using QLoRA with 4-bit quantization. Only 0.045% parameters updated.
Weather-aware AI agent using Model Context Protocol with real-time APIs and FastAPI.
LangChain RAG pipeline processing .txt, PDF, and web documents with source tracing.
Multivariate LSTM model for air pollution forecasting. Achieved 0.099 RMSE.
Comprehensive skill set spanning the entire ML/AI pipeline
Python
Java
JavaScript
C++
SQL
PyTorch
TensorFlow
Keras
Scikit-learn
Apache Spark
Transformers
QLoRA / LoRA
PEFT
TRL / SFT
Prompt Engineering
LangChain
LangGraph
CrewAI
MCP
FAISS / Pinecone
Docker
Kubernetes
AWS / GCP
FastAPI
CI/CD
MLflow
Weights & Biases
Apache Airflow
Apache Kafka
dbt
Quantization
Groq Inference
Low-latency Serving
Streaming
bitsandbytes
Tableau
Power BI
Matplotlib
Plotly
Seaborn
Interested in AI, machine learning, or potential collaborations? I'd love to hear from you.