• Designed, trained, and scaled ML systems for enterprise use cases, serving hundreds of partner teams

• ML research efforts involve LLMs, agents, CNNs, time series models, root cause analysis

• Delivered embedded production software to improve feedback control algorithms and robot operating systems

• Invented novel algorithm to increase robot safety

• Researched machine learning models for robotic data analysis, including designing autoencoders for anomaly detection and custom neural networks for failure prediction

• Automated E2E testing for CI/CD, saving dev time and increasing team productivity

• Worked on rendering, A/B testing, scalability, system design, and cloud computing

• Developed machine learning models using time series data from robotic systems

• Built data pipeline with parallel computing for data pre-processing

• Exposure to teleoperation control algorithms and software architecture