Palak Harinkhede

AI Engineer & Multi-Agent Systems Specialist

LLMs • Agentic AI Workflows • RAG Systems • Machine Learning

AI Engineer @ STMicroelectronics

Enterprise RAG Pipelines • Vector Search (FAISS) • Function Calling • PyTorch • Deep Learning

Explore Projects Contact Me

About Me

Palak Harinkhede

AI Engineer (M.Tech CSE @ DTU) specializing in Agentic AI & RAG Systems

I specialize in architecting Production LLM Applications, Retrieval-Augmented Generation (RAG) pipelines, and Multi-Agent Workflows that automate complex enterprise decision-making. My expertise covers vector search (FAISS), function calling, fine-tuning, time-series forecasting, and computer vision.

Multi-Agent AI
RAG & Vector DBs
LLMs & PyTorch

"Engineering the future with Agentic AI, neural networks, and scalable pipelines."

Featured Projects

Interactive gallery showcasing AI/ML projects that push the boundaries of what's possible

Voice Finance Buddy

Multi-Agent Financial Assistant featuring Speech-to-Text (Whisper), GPT-4 intent routing, and sub-3s interaction latency.

Python GPT-4 Whisper RAG FAISS Streamlit
Live Demo

DocQuery AI

Enterprise Document Intelligence RAG system built with Sentence Transformers, local LLMs (TinyLlama), and FAISS indexing.

Python FAISS Sentence Transformers TinyLlama Streamlit
Live Demo

AI Demand Forecasting

Supply chain forecasting platform built with Prophet time-series prediction, EOQ, and Reorder Point (ROP) optimization.

Python Prophet Pandas NumPy Streamlit
Live Demo

SnippetVault

Full-stack developer code snippet manager for storing, tagging, and instantly searching reusable code snippets.

Next.js TypeScript TailwindCSS Railway
Live Demo

MoodBeat AI

Emotion-Aware Music Recommendation engine powered by CNN facial affect recognition from webcam video feeds.

Python CNN OpenCV TensorFlow
Live Demo

Pothole Detection System

Real-time road defect identification using YOLOv4 computer vision for automated infrastructure inspection.

Python YOLOv4 OpenCV TensorFlow
GitHub Repo

Experience Timeline

My journey in data science, artificial intelligence, and software engineering

AI Project Trainee

STMicroelectronics, Noida • Predictive Modeling & Anomaly Detection
Jul 2025 – Dec 2025 (6 Months)
  • Developed industrial machine learning pipelines using Random Forest, XGBoost, and CatBoost for predictive analytics and anomaly detection on high-dimensional manufacturing datasets.
  • Engineered feature extraction, automated time-series forecasting, hyperparameter tuning, and real-time inference monitoring workflows.
Python Random Forest XGBoost CatBoost Time-Series

AI Project Trainee

STMicroelectronics, Noida • Agentic AI Workflows for PLM Automation
Jan 2026 – Jul 2026 (6 Months)
  • Designed and developed multi-agent AI workflows for Product Lifecycle Management (PLM) automation using LLMs, function calling, and intelligent task routing.
  • Built retrieval (RAG), reasoning, and structured data processing pipelines integrating enterprise knowledge sources and semantic search.
Python LLMs Agentic AI Workflows Function Calling RAG & FAISS

Technical Skills

Full competencies, frameworks, tools, and algorithms pulled from resume

Generative AI & LLMs

Large Language Models (LLMs) Agentic AI Multi-Agent Systems Retrieval-Augmented Generation (RAG) Prompt Engineering Function Calling NLP Multimodal AI Model Fine-Tuning AI Agent Orchestration

Retrieval & Vector Search

FAISS Semantic Search Vector Databases (FAISS) Vector Search Query Expansion Information Retrieval RAG Pipelines Vector Indexing Sentence Transformers

Machine Learning & Computer Vision

Machine Learning Deep Learning Time-Series Forecasting Anomaly Detection Predictive Analytics Computer Vision CNNs Image Classification Object Detection (YOLO) Operational Analytics

Frameworks & Libraries

PyTorch TensorFlow Scikit-learn XGBoost CatBoost OpenCV Pandas NumPy Hugging Face Transformers

Languages, Tools & Core CS

Python C++ Streamlit Git & GitHub Linux Data Structures & Algorithms OOP Operating Systems DBMS System Design Scalable AI Systems

Education & Credentials

2024 – 2026

M.Tech in Computer Science Engineering

Delhi Technological University (DTU)

CGPA: 8.5 / 10
2018 – 2022

B.E. in Computer Science Engineering

Sinhgad College of Engineering, Pune

CGPA: 8.85 / 10 (Honours in AI & ML)

Let's Connect

Ready to collaborate on the next big AI innovation? Let's build something amazing together.

Send a Message

"Ready to process your ideas into reality!"

palakharinkhede1@gmail.com +91 9673494515 GitHub Profile LinkedIn Profile