
AI Engineer with less than a year in RAG Pipelines, LLM Fine-tuning & MLOps.
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Highly motivated AI/ML Engineer with 0.8 years of hands-on experience in developing and deploying intelligent systems. Expertise includes building GeoSpatial AI platforms with RAG pipelines, fine-tuning LLMs with LoRA/QLoRA, and containerizing inference stacks with Docker on AWS. Proven ability to reduce hallucination, optimize inference, and maintain high production uptime. Strong foundation in machine learning, deep learning, NLP, and MLOps, coupled with a passion for leveraging AI to solve complex problems.
Shri Ram Group of College
Bachelor of Technology · Artificial Intelligence and Machine Learning
August 1, 2024 – June 30, 2028
Steve's AI Lab
AI/ML Engineer
April 1, 2026 – Present
Indore, Madhya Pradesh, India
Techieshubhdeep Pvt. Ltd.
AI/ML Intern
April 1, 2025 – January 1, 2026
Gwalior, Madhya Pradesh, India
RAG Document Search System
June 1, 2026 – Present
Built a production RAG pipeline using LangChain and FAISS for semantic search and context-aware document Q&A. Developed async FastAPI services for document ingestion, text chunking, and Hugging Face embedding generation. Improved retrieval precision via cosine similarity re-ranking, outperforming keyword-based BM25 baselines.
View ProjectAI Resume Analyzer & Job Matcher
June 1, 2026 – Present
Built an NLP resume screener using NER-based skill extraction and TF-IDF cosine similarity against JD. Designed Scikit-learn pipelines for keyword extraction, skill matching, and automated candidate scoring and ranking. Deployed Streamlit web app with SQLite history, reducing manual resume screening effort by ~60%.
View ProjectFitness LLM Mistral 7B Instruct
June 1, 2026 – Present
Fine-tuned Mistral-7B-Instruct on a fitness Q&A dataset using QLoRA (4-bit quantization + LoRA via PEFT/Unsloth). Achieved 3× faster training vs. full fine-tuning using gradient checkpointing and mixed-precision on <12 GB VRAM. Deployed domain-adapted LLM to Hugging Face Hub for public inference with context-aware fitness guidance.
View ProjectAWS Machine Learning Foundations
Udacity
June 1, 2026 – Present
ChatGPT Prompt Engineering for Developers
DeepLearning.AI
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from RAG systems to resume analyzers and fitness LLMs, indicates a broad interest in AI applications. Their current role as an AI/ML Engineer and previous internship align well with the target AI Engineer role, suggesting a strong commitment to the field. The use of various open-source tools and platforms (Hugging Face, Streamlit, GitHub) points to a collaborative and community-oriented mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations and a proactive approach to learning new technologies, as evidenced by certifications and diverse project work. Their experience in deploying and monitoring AI systems suggests an understanding of operational requirements and reliability.