May 2025 – Aug 2025 · 3 mos · Bengaluru, Karnataka, India · On-site

• Contributed to a high-impact agentic AI project within the Workspace team. My work focused on enhancing model efficiency, evaluation, and scalability.
• Accelerated agent performance evaluation by 100x by developing an LLM-as-a-judge automation tool, reducing multi-hour accuracy testing to under a minute.
• Reduced knowledge base onboarding time by 90% (from weeks to a single day) by engineering a standardized, ADK-based ingestion pipeline.
• Decreased prompt token usage by 60% (from ~10k to ~4k tokens) by implementing a dynamic RAG-based tool for on-demand context injection.
• Boosted team evaluation efficiency by 10x by creating a multi-threaded shell script to parallelize Colab notebook evaluations, overcoming intern permission constraints.

Sep 2024 – Jun 2025 · 9 mos · Kota, Rajasthan, India · On-site

• As the AI/ML Lead for Google Developer Group on campus IIIT Kota, I'm responsible for driving AI and Machine Learning initiatives within our tech community. My role involves:
• Organizing and leading hands-on workshops and project-based learning experiences in AI/ML
• Guiding members in developing practical AI/ML projects, focusing on areas like computer vision and neural networks
• Expanding interest and knowledge in AI/ML across the campus community
• Fostering collaboration and knowledge sharing among students and tech enthusiasts
• Planning and executing events to enhance AI/ML skills and awareness
• Bridging the gap between theoretical concepts and practical applications in AI/ML
• Collaborating with other GDG leads to create a comprehensive learning environment
• Staying updated with the latest trends and technologies in AI/ML to provide cutting-edge knowledge to our members
• This role allows me to combine my passion for AI/ML with leadership and community building, contributing to the growth of our tech ecosystem at IIIT Kota.

Mar 2024 – Jun 2024 · 3 mos · Remote

• As an Artificial Intelligence Intern at Infosys Springboard, I was part of a dynamic team developing an innovative Energy Consumption Forecasting System. This role provided hands-on experience with the full machine learning lifecycle and exposure to industry-leading AI/ML practices.
• Key Responsibilities:
• Contributed to the development of a machine learning-based Energy Consumption Forecasting System
• Participated in data collection, preparation, and preprocessing activities
• Assisted in feature engineering and selection processes
• Collaborated on model training, evaluation, and optimization
• Worked with team members to ensure scalability and robustness of the AI solution
• Engaged in regular knowledge-sharing sessions and progress reviews with mentor
• Skills Developed:
• Advanced Python programming for data science and machine learning
• Proficiency in data analysis and visualization techniques
• Practical experience with machine learning frameworks and libraries
• Understanding of feature engineering and algorithm selection methodologies
• Exposure to best practices in developing scalable AI solutions
• Enhanced problem-solving and critical thinking skills in an AI context
• Improved collaboration and communication in a remote team environment
• Achievements:
• Successfully contributed to the completion of the Energy Consumption Forecasting System project
• Gained comprehensive understanding of the machine learning development process in a real-world setting
• Developed a strong foundation in AI/ML principles and practices
• Received mentorship from experienced data scientist and AI professionals
• This internship provided invaluable experience in applying theoretical knowledge to practical AI development, setting a strong foundation for future career growth in the field of artificial intelligence and machine learning.