Lead Engineer (April 2025 - Aug 2025)

• Leading a cross-functional squad of 8 engineers (Frontend, Backend, and AI engineer) in the AI team, overseeing quarterly roadmap planning and technical execution.
• Splitting my time as a hands-on AI Engineer, currently contributing to the development of the AI agents feature.

Machine Learning Engineer III (January 2024 - March 2025)

• Developed and successfully delivered Sentiment Analysis Phase I, including modeling and generating key analytics reports, laying the foundation for ongoing customer-facing insights.
• Directed the development of a comprehensive suite of LLM-based Agent Co-Pilot features (Issue Summary, Suggested Response, and Smart Compose)
• Key contributor to the backend architecture guild at Helpshift to support critical cross-functional initiatives.
• Drove improvements in team efficiency and project delivery through direct mentoring of junior developers, leading sprint calls, and optimizing quarterly capacity planning for multiple AI features.

Machine Learning Engineer II (March 2022 - December 2023)

• Led a project utilizing LLM-based RAG implementation to address common user queries efficiently.
• Developed a KNN-based recommendation feature, improving user intent determination for customer support.
• Analyzed performance metrics for the user intent classification service, enabling automated intent determination.
• Built an analytics pipeline to enhance ML Observability for existing ML services.
• Interviewed, onboarded, and mentored three junior engineers in the team.

Software Engineer II (January 2022 - February 2022)

• Led mobile SDK delivery for Unity and Unreal Engine

Software Engineer I (January 2021 - December 2021)

• Delivered a major release for mobile SDK by leading business-critical projects like feedback bots and Unity VSP.
• Mitigated customer pain points during SDK integration, enhancing developer experience and satisfaction.

Associate Software Engineer (October 2019 - December 2020)

• Optimized AWS spend, saving $2.5M annually through analytics and configuration improvements.
• Analyzed 1.4M fatal SDK logs using Pandas and NumPy to identify actionable tech tasks.

• Academic curriculum-integrated internship
• Engineered an automated Python bug triage system utilizing multivariate analysis, cutting NVIDIA Capture SDK bug investigation time by approximately 26%.
• Developed a Python GUI tool for Event Tracing for Windows (ETW) log analysis to accelerate debugging workflows.

• Remote internship focused on data analytics and business intelligence
• Applied data analytics concepts to solve real-world business challenges
• Worked on Harvard Business Review case studies and airline industry project analysis

• Internship under Prof. Sameer Mathur in Data Analytics & Applications
• Applied data analysis and visualization techniques to real-world business challenges
• Worked on Harvard Business Review case studies and airline industry project
• Developed proficiency in data analytics concepts and business problem-solving