Jayanth Thilagar

Architect

Persistent Systems•  January 2024 - Present•  Bengaluru, India

- Collaborated with data scientists, product team, and management to build next-gen AI platform. - Developed a graph-based recommendation system integrating NLP and GenAI models. - Applied advanced NLP techniques to extract entities and relationships from unstructured text data, feeding insights into a Neo4j graph database for enhanced data connectivity and visualization. - Designed and implemented a knowledge graph to enhance the company’s chatbot capabilities, improving user query resolution time by 30%. - Integrated Neo4j with NLP models to extract and visualize key insights from unstructured data, supporting strategic decision-making - Designed and executed graph algorithms for text clustering and topic modeling, enabling more accurate and insightful text analysis. - Utilized RAGAS to assess the retrieval quality and adaptive sampling effectiveness, enabling more accurate and contextually relevant text outputs from GenAI models. - Delivered presentations and visualizations using Neo4j Bloom and other tools to communicate complex graph structures and NLP findings to non-technical stakeholders.

Software Engineer

NCS Pte Ltd•  October 2018 - August 2023•  Singapore

- Expertise in Python, implementing OOP principles to develop robust and maintainable software solutions. - Designed and implemented machine learning models for predictive analytics, including regression, classification, and clustering, to optimize business operations. - Utilized feature engineering, Bayesian methods, decision trees, and ensemble techniques to improve model accuracy and performance. - Developed data-driven dashboards and reports, enhancing decision-making processes for stakeholders. - Implemented MLOps design patterns and tooling, including Google Vertex AI, and GitLab CI/CD pipelines. - Spearheaded anomaly detection projects to identify outliers in the financial transactions. - Leveraged SQL for data extraction and analysis, streamlining data retrieval processes and reducing query time by 30%. - Implemented machine learning projects from initiation to deployment with a focus on automation and optimization. - Managed data observability using ElasticSearch, ensuring data accessibility and reliability.

ITO Consultant

Hewlett Packard Enterprise•  December 2016 - July 2017•  Chennai,India

- Designed, built, and maintained scalable and robust infrastructure for AI/ML systems, including cloud-based environments on AWS. - Developed and implemented CI/CD pipelines using tools like GitLab CI/CD to automate the deployment, testing, and monitoring of AI/ML models and applications. - Collaborated with data scientists, data engineers, and software engineers to optimize model training, deployment, and inference pipelines, reducing time-to-deployment by 20%. - Monitored and troubleshooted AI/ML systems to ensure high availability, performance, and reliability, achieving 99.9% uptime.