Rahul Patil

Lead ML Engineer

Kolhapur, Maharashtra, India1 yr 10 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Developed AI solutions for real-world airline workflows.
Passionate about Machine Learning and Deep Learning technologies.
Eager collaborator in tech community projects.

Stackforce AI infers this person is a Machine Learning Engineer with a focus on SaaS applications.

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Skills

Core Skills

Machine LearningDeep Learning

Other Skills

Mistral AI LLMGoogle Colab GPUStreamlitFastAPILangChainPythonPrompt EngineeringOllamaHugging Face modelsGitHubData Structures and Algorithms(DSA)SQLDatabase Management System (DBMS)OpenAI APILarge Language Models (LLM)

About

I am a final-year student pursuing a B.E. in Electronics and Telecommunications Engineering at Pune Institute of Computer Technology (PICT), Pune. I have a deep interest in Machine Learning (ML), Deep Learning (DL), and Generative AI, and I love exploring how these technologies can drive innovation and solve real-world problems. Along with AI, I am also passionate about core computer science subjects such as Database Management Systems (DBMS), Computer Networks, and Operating Systems. I am always eager to learn, collaborate on projects, and connect with like-minded individuals in the tech community

Experience

1 yr 10 mos

Total Experience

1 yr 10 mos

Average Tenure

1 yr 10 mos

Current Experience

Housedeal limited

AI/ML Engineer

Aug 2025 – Present · 10 mos · Pune, Maharashtra, India · Remote

Fareintelligence

AI/ML Engineer

Jun 2025 – Aug 2025 · 2 mos · Pune, Maharashtra, India · On-site

I first worked on building a full-stack Air Shopping Assistant using the Mistral AI LLM to handle NDC-based airline workflows like AirShopping, OfferPrice, OrderCreate, SeatAvailability, and OrderCancel. We deployed the model in quantized form on Google Colab GPU and connected it with a Streamlit front-end and FastAPI backend to give instant NDC responses and airline suggestions.
After this, I developed an AI-powered Test Case Generator for NDC scenarios using a 4-bit quantized LLaMA 3 model with a Python backend and Streamlit UI. It created scenario-specific test cases (AirShopping, OfferPrice, OrderCreate) using structured prompting with LangChain, making test coverage and validation much faster and easier.

Mistral AI LLMGoogle Colab GPUStreamlitFastAPILangChainPython+2