Feb 2024 – Nov 2024 · 9 mos · Mountain View, California, United States · Hybrid

• > First engineer, Led AI product development, from prototyping to implementation of Compound AI System driving innovative solutions and feature integration.
• > Developed advanced LLM methodologies for dense search and retrieval, hybrid RAG, document analysis, and function calling, along with summarizing and data extractions from multimodal documents.
• > Designed and implemented AI Agents, by building architecture for multi-agent collaboration.
• > LLM evaluation frameworks, combining custom metrics, LLM-as-judge, and synthetic data generation for evaluating models.
• > Built AI System to generated research-driven reports by integrating multi-modal data, extracting insights and via IDP, domain-reasoning prompts etc.

Jun 2023 – Aug 2023 · 2 mos · Menlo Park, California, United States · Remote

• ◦Significantly enhanced process analyst bot capabilities through focused testing and refining of Language Learning Models (LLMs), ensuring improved performance.
• ◦ Thoroughly curated several versions of domain and task specific dataset by deeply investigation and researching on product specs and targets.
• ◦Conducted in-depth exploration of diverse Language Models, identifying their potential for our process analyst bot. Trained and fine-tuned SLMs (BERT, TAPEX, TAPAS) and LLMs (LLAMA models) using Pytorch-Lightning.
• ◦Achieved a remarkable ~30% accuracy boost by strategically applying domain adaptation and masked learning techniques enhancing the model(s) performance.

May 2023 – Oct 2023 · 5 mos · Stony Brook, New York, United States · On-site

• ◦Examining the co-occurrence of Chronic Kidney Disease within the National COVID Cohort Collaborative (N3C) dataset for Y2 Q3.
• ◦Conducting an inquiry into the correlation between acute COVID-19 cases and the advancement of pre-existing chronic kidney disease (CKD) in adults. Investigating both COVID-positive and COVID-negative cohorts.
• ◦Employed Pyspark and SQL to transform and analyze a dataset of 16 million patient records. Utilized these transformations for two purposes:
• comparing post-COVID CKD progression against a composite benchmark,
• and assessing changes in eGFR values before and after COVID infection.

Jan 2023 – Dec 2023 · 11 mos · Stony Brook, New York, United States · On-site

• Leveraged Large Language Models (LLMs) to extract insights from unstructured medical notes for clinical applications.
• Processed Electronic Fetal Monitoring (EFM) data, anonymized sensitive information, and utilized PostgreSQL and Python for dataset creation.
• Developed text2sql engine for clinicians to access patient data using Language Models.
• Applied predictive analytics to improve EFM data interpretation.

Feb 2022 – Mar 2022 · 1 mo · Remote

• ◦Taught basics of Artificial Intelligence, Machine Learning and Python programming language.
• ◦ Provided guidance and oversight on hands-on projects.
• ◦ Assisted in creating course plans, material prep and implemented them to ensure quality learning for students

May 2021 – Mar 2022 · 10 mos · Solan, Himachal Pradesh, India

May 2021 – Jun 2021 · 1 mo

• ◦ Collaborated with team of 6 people for developing a machine learning based detection system.
• ◦ Achieved reduction in training time of the model, by incorporating different feature extraction techniques on data.
• ◦ Implemented a variety of machine learning algorithms to evaluate the performance of the model on processed data

Jul 2020 – May 2021 · 10 mos · Solan, Himachal Pradesh, India · On-site

Apr 2020 – Jul 2020 · 3 mos · Gurugram, Haryana, India

• ◦ Reviewed software requirements and designed test case scenarios to perform testing on Android and iOS Mobile
• applications.
• ◦ Prepared reports on tests carried out for development team to resolve bugs and check the usability of the software.
• ◦ Participated in design reviews and provided input on required product design, and potential problems