New Delhi, Delhi, India
•Fine-tuned open-source Large Language Models (LLMs), including Gemma, utilizing instruction tuning and parameter-efficient techniques (LoRA) to optimize performance on domain-specific enterprise datasets. • Architected and deployed agentic AI workflows, integrating LLM reasoning capabilities with external toolsets to automate complex analytical tasks and streamline internal knowledge retrieval. • Engineered robust AI guardrails and validation layers—incorporating prompt constraints, response filtering, and rigorous evaluation protocols—to ensure high-fidelity, safe, and reliable model outputs.
• Processed and visualized client datasets using Python libraries such as Pandas and Seaborn to support exploratory data analysis. • Gained hands-on experience in machine learning by training and evaluating regression, classification, and forecasting models on real-world business data. • Collaborated with senior team members on model experimentation and project execution, utilizing Git and Jupyter for efficient version control and reproducible workflows.
• Contributed to backend system maintenance and overall application stability by debugging code, writing unit tests, and resolving 15+ software bugs. • Collaborated within an agile team environment, utilizing Git for efficient version control and secure deployment.