Transforming Sales Operations through Generative AI InnovationLeading the architecture and development of enterprise-scale generative AI solutions that revolutionize sales operations at NVIDIA. Spearheading multiple mission-critical projects including:Architecting and building SASIE, a production grade RAG based advanced sales literature chatbot enabling AI-powered access to sales content across Nvidia. Featured on LlamaIndex and Nvidia Technical blogs. https://www.llamaindex.ai/blog/case-study-building-an-ai-sales-assistant-with-llamaindex-and-nvidia-nimDeveloping an agentic Text-to-SQL framework that bridges Databricks, NVIDIA NeMo, and Azure OpenAI, empowering sales teams with natural language access to complex business dataBuilding scalable microservices that integrate generative AI capabilities into Salesforce support systems, significantly reducing ticket resolution time and enhancing support efficiencyExpert in large language model deployment and optimization, with hands-on experience managing production workloads on NVIDIA A100s and integrating various LLM architectures (Llama, Mistral) for enterprise use cases. Skilled in designing RAG-based systems, Agentic workflows, vector databases (Milvus, Pinecone), and enterprise knowledge management solutions.Passionate about creating practical AI solutions that drive business value while maintaining enterprise-grade security, scalability, and performance standards. Consistently collaborating across teams to deliver innovative solutions that enhance sales productivity and customer experience.

I served as the Head of AI in a cross-functional role, where I led a diverse team of engineers, PhDs, and data scientists, fostering a culture of innovation and excellence. I not only provided technical leadership but actively engaged in hands-on development. My responsibilities also included direct interactions with customers, investors and the c-level executives. In my day-to-day work, I was deeply involved in the entire pipeline of full stack machine learning from development to deployment of custom AI solutions. I pioneered various NLP techniques, including LLMs (medical coding), transformers (quality reporting), and GPT (disease progression). A preprint of my latest paper using LLM is available on arXiv (https://arxiv.org/abs/2310.04595)I also led the development of a comprehensive healthcare platform and real-time insights tools, scaling to 40 million individuals, leading to proactive interventions for high-risk patients and cost savings of $50 million.

Developed a drug-drug interaction app - orchestrated with streamlit, which detects drug interactions for a molecule with 90% accuracy.Leveraged keras, python, streamlit and AWS to build an end to end ML pipeline with a custom ’CNN-LSTM with attention’ architecture.

Over the course of my 10-year career at Saama, I played a pivotal role as a data scientist and machine learning consultant with a strong customer-facing focus at renowned companies like Genentech, Actelion, Gilead Sciences, Dignity Health, and Cisco.I worked on a broad spectrum of projects in different industries, Deep Learning Engineer at Gilead Sciences: Deployed an end-to-end ML pipeline for infection detection, conceptualized a CNN-based vision inspection system with strict inference time constraints, and improved field reps' efficiency using Google's Dialogflow virtual assistant.NLP Engineer at Dignity Health: Led a team to develop a custom full-stack Python application for social media data analysis, mining large structured and unstructured datasets to provide actionable insights via customized dashboards.Data Engineer at Actelion Pharmaceuticals: Worked on risk estimation and mitigation reports for FDA compliance, and deployed sales reports for 250 representatives using Roambi on iOS with a Microsoft SQL backend.Data Scientist at Cisco: Designed a customer dashboard with 50+ KPIs and shipment forecasting, developed a semi-supervised customer segmentation model with interpretable results, and implemented a Python-based time series change point detection system for uncovering trend changes in customer metrics.Founder open source project: I've contributed to open source focused on analyzing Twitter data for disease-related insights.

I founded a project that used machine learning to analyze tweets for insights into public health. Formed a global community of 200+ innovators from 25 countries, focused on improving healthcare using data science on social media. My effort spanned 1000+ hours over 2 years, and inspired many to pursue data science careers in healthcare and even led to one participant launching their healthcare firm. As a leader on this initiative, I have forged valuable connections in various industries, and to this day, colleagues from this community approach me for advice on machine learning projects and startups.