Tejas Nama

Tejas Nama is a seasoned machine learning professional with extensive experience in developing and implementing machine learning models across various domains. Career highlights include roles at Nutanix, where Tejas focused on tree-based models and neural networks for latency prediction, and IGCAR, where a support vector machine model was developed for flaw detection in nuclear fuel pins. Subsequent positions at SambaNova Systems involved managerial responsibilities and advanced model development, while contributions at Qubole included customer behavior analysis using clustering techniques. Currently serving as a Machine Learning Engineer at Meta, Tejas continues to optimize large language models for performance on GPUs and TPUs. Tejas holds a Bachelor of Engineering in Computer Science from the Birla Institute of Technology and Science and a Master's in Computational Data Science from Carnegie Mellon University.