AI Engineer & Researcher with 3+ years of experience building Machine Learning and Generative AI systems across NLP, LLMs, computer vision, and multi-agent workflows.
I enjoy solving real-world problems where models need to be scalable, reliable, and trusted by users.

• Large Language Models (LLMs) – fine-tuning, RAG, agents, evaluation
• NLP Systems – summarization, semantic search, clustering, classification
• Time-Series & Anomaly Detection – risk, fraud, observability-style problems
• Multi-Agent Architectures – orchestration, decision-making, automation
• MLOps & Deployment – FastAPI, Docker, CI/CD, monitoring

Fine-tuned multilingual LLMs for Sanskrit translation & QA

• Fine-tuned Gemma-2-9B and LLaMA-3.1-70B
• Improved BLEU, ROUGE, and semantic similarity by up to 40%
• Focused on evaluation, prompt design, and inference optimization
  🔗 Repo: Coming soon / link here

AI companion for Gen Z mental well-being

• Built RAG pipelines using LangGraph, Cohere embeddings & ChromaDB
• Integrated agentic workflows and deployed via Streamlit
• Achieved ~90% response relevance accuracy
  🔗 Repo: Coming soon / link here

Detecting synthetic voices using audio ML

• Used ASVSpoof datasets, mel-spectrogram features & CNNs
• Achieved 98% detection accuracy
• Extended analysis to multilingual deepfake audio
  🔗 Repo: Coming soon / link here

• Built and deployed ML systems used in real enterprise workflows
• Designed REST APIs using FastAPI, containerized with Docker
• Experience with ML lifecycle management, monitoring & iteration
• Worked across AWS, Azure, and GCP

• CLEF 2025 – CheckThat! Lab (Working Notes)
  • Fine-tuning & zero-shot approaches for claim normalization
  • Ranked 3rd (Hindi) and 4th (Telugu) among global teams

Languages & ML: Python, PyTorch, TensorFlow, Scikit-learn
LLMs & GenAI: LangChain, LangGraph, PEFT/LoRA, RAG, Agents
MLOps: FastAPI, Docker, Kubernetes, MLflow, Airflow
Data & Cloud: SQL, ChromaDB, DuckDB, AWS, Azure, GCP