Rajesh Thallam
Co-founder & CTO at EnsureCare
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolRajesh Thallam is a Co-founder and CTO with 7+ years of focused experience architecting large-scale AI infrastructure that trains and serves foundation models across 2K+ GPU/TPU clusters using Slurm and Kubernetes. At Google he bridged research and production by publishing optimized training and inference recipes (NeMo, MaxText, vLLM, NVIDIA Dynamo) and driving customer success for Google Gemini launches and agentic coding workflows like SWE-Agent. He combines deep systems expertise—roofline analysis, distributed checkpointing, multi-host disaggregated serving—with hands-on MLOps and benchmarking that routinely squeezes higher TFLOPs utilization from complex stacks. Rajesh is an active open-source maintainer for Google Cloud integrations (LangChain, LlamaIndex) and contributes to high-profile projects such as tensorflow/tfjs, improving usability and stability for web ML. Based in San Francisco, he helps startups, research labs and Fortune 500s move models from prototype to production and has a habit of turning enterprise feedback into product roadmaps for pre-GA cloud ML services.
7 years of coding experience
17 years of employment as a software developer
Master’s Degree, Master of Information and Data Science (MIDS), Master’s Degree, Master of Information and Data Science (MIDS) at UC Berkeley School of InformationPost Graduate Diploma in Business Administration, Finance, General, Post Graduate Diploma in Business Administration, Finance, General at Symbiosis Institute of Management StudiesBachelor of Engineering (B.E.), Electronics and Communication Engineering, Bachelor of Engineering (B.E.), Electronics and Communication Engineering at Chaitanya Bharathi Institute of Technology (Osmania University)
Github Skills (12)
tensorflowjs10
machine-learning10
javascript10
typescript-types9
deeplearning-ai9
typescript9
neural-network9
typescripts9
deep-learning9
python8
webassembly5
webgl4
Programming languages (8)
Github contributions (5)
tensorflow/tfjs
Oct 2019 - Aug 2022
A WebGL accelerated JavaScript library for training and deploying ML models.
Role in this project:
ML Engineer
ML EngineerContributions:6 reviews, 40 commits, 52 PRs in 2 years 11 months
Contributions summary:Rajesh primarily contributes to the TensorFlow.js library by addressing bugs, enhancing existing features, and improving the overall functionality. Their work includes fixing issues related to model saving with HTTP requests, updating the SavedModel implementation, and addressing deprecation warnings in NumPy type usages within the conversion tools. Furthermore, the user added functionality to activation configurations and made various updates to testing and converter files. The contributions are focused on enhancing the usability and stability of the library.
javascriptmlmodelwebgldeep-learningtypescript
rthadur/tfjs-models
Aug 2019 - Aug 2022
Pretrained models for TensorFlow.js
Contributions:27 pushes, 11 branches in 3 years
javascriptmachine-learningpretrained-modelstensorflowtensorflow-js
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