Sai S
Software Engineer at Google
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolSai S is a software engineer with 8 years of experience specializing in applied machine learning and production-grade MLOps, currently building Food Ordering AI agents at Google. He has a strong track record delivering end-to-end LLM solutions and platform engineering—hosting Triton, Airflow, MLflow, Ray and vector DBs—to enable MLOps for 15+ clients and turn demos into paid engagements. Previously he optimized conversational AI and spell-check models at Microsoft/Nuance, shipping latency and accuracy improvements, and built OCR + BERT-NER pipelines that scaled with PySpark for healthcare analytics. Comfortable across research and product settings, Sai bridges model innovation with reliability in production, troubleshooting service-mesh and infra incidents under pressure. He holds advanced AI training from Mila/Université de Montréal and a CS degree from IIT Bombay, combining rigorous academic grounding with practical systems experience.
8 years of coding experience
3 years of employment as a software developer
Intermediate Education Physical Sciences, Intermediate Education Physical Sciences at Sri Chaitanya Narayana Institution, HyderabadMaster of Science - MS Computer Science, Master of Science - MS Computer Science at Mila - Quebec Artificial Intelligence InstituteIndian Institute of Technology BombayMasters of Science Computer Science, Masters of Science Computer Science at Université de MontréalSecondary Education, Secondary Education at Sri Chaitanya Techno School
English, Hindi, Telugu
Github Skills (24)
pytorch10
python10
machine-learning10
deep-learning10
tensorflow10
natural-language-processing10
transformer10
speech-recognition10
nlp10
transformers9
language-model9
bert9
tesseract9
lstm9
jax9
Programming languages (4)
Github contributions (5)
saikalyan9981/SPADE-Breast-Cancer-Segmentation
May 2022 - May 2022
Contributions:4 commits, 2 pushes, 2 branches in 1 day
saikalyan9981/macro-action-rl
Feb 2020 - Jun 2020
An implementation of five reinforcement learning algorithms to simulate macro actions for the HFO problem.
Contributions:28 pushes, 1 branch in 3 months
reinforcement-learning-algorithmsreinforcement-learninglearning-algorithmsmacroproblem
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