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Aditya Gautam

@adityagautam

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AI/ML engineer focusing on scalable ML systems, RAG, and applied deep learning for production-ready solutions.

India

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What I'm looking for

I seek roles building production-ready ML/AI systems where I can apply RAG, deep learning, and MLOps practices, contribute to scalable pipelines, and grow in system design and deployment.

I am an AI/ML engineer with hands-on experience building production-oriented ML systems, RAG chatbots, and deep learning models. I deliver privacy-aware, offline solutions and scalable data pipelines that improve latency and QA performance.

During a machine-learning internship at Bharat Electronics Ltd., I built DocSense, an offline RAG chatbot using Ollama, LangChain, and ChromaDB, engineered chunking and embedding pipelines to cut query latency by 30%, and implemented table and image parsers to raise non-text QA accuracy by ~25%.

Outside internships, I developed several projects including a modular quantitative trading system with a full backtesting engine (achieving simulated annual returns of 18–27%), a multi-service AI productivity platform with CI/CD and Docker deployment, and a CNN-based dog-breed classifier that improved validation accuracy from 85% to 93%.

I hold research and competition credentials (IEEE publication, Adobe Hackathon) and a Google Cloud Professional Data Engineer certification. I seek roles where I can apply ML/AI expertise to deliver robust, production-grade systems and continue learning MLOps and scalable ML deployments.

Experience

Work history, roles, and key accomplishments

Current

AI/ML Intern

Current

Swaja Robotics

Jun 2026 - Present (1 month)

Developing a lightweight RCNN (CNN+LSTM) glass-break detection model using Mel-spectrogram features. Optimizing a real-time offline inference pipeline for Raspberry Pi Zero and extending support for additional acoustic classes such as sirens, fire alarms, and baby crying.

Mel Spectrogram Features Raspberry Pi Zero Deployment Model Extensibility

ML / AI Engineering Intern

Bharat Electronics Ltd.

Jul 2025 - Aug 2025 (1 month)

Built DocSense, an offline RAG chatbot for querying internal PDF documents using Ollama, LangChain, and ChromaDB with zero cloud dependency. Reduced query latency by 30% and improved non-text QA accuracy by ~25% via chunking/embeddings and specialized table/image parsers for privacy-secure defence environments.

Offline RAG Ollama ChromaDB Embeddings Image Extraction Lang Chain

ML Intern

Bharat Electronics Ltd.

Jul 2025 - Aug 2025 (1 month)

Built DocSense, an offline RAG chatbot using Ollama, LangChain, and ChromaDB to query local PDFs; engineered a scalable ingestion pipeline that cut query latency by 30% and improved non-text QA accuracy by ~25% via table and image parsers.

Lang Chain ChromaDB Ollama Embeddings Data Ingestion PDF Parsing Python RAG

Education

Degrees, certifications, and relevant coursework

Ajay Kumar Garg Engineering College

Bachelor of Technology, Computer Science and Engineering (AI/ML)

2022 -

Grade: 8/10

Pursuing a Bachelor of Technology in Computer Science and Engineering (AI/ML) with coursework in Deep Learning, NLP, and Data Structures & Algorithms and a cumulative GPA of 8/10.