Valliappa Lakshmanan
Co-Founder And CTO at ObinAI
Bellevue, Washington, United States
Summary
🤩
Rockstar🎓
Top School
Top expert inGoogle Cloud Platform Development Essentials
Valliappa Lakshmanan is a Co-Founder and CTO of Obin AI and an O'Reilly author with 10 years of industry experience driving data, ML and cloud platforms. He blends hands-on ML engineering—demonstrated by contributions to GoogleCloudPlatform repos that accompany O'Reilly books (Data Science on GCP, Machine Learning Design Patterns, BigQuery)—with product and platform leadership from roles at Google and Silver Lake. His work spans production data pipelines and BigQuery ingestion, TFRecord/TPU training pipelines, image-captioning and embedding-based retrieval, and practical deployments of Keras/TensorFlow models. He also brings uncommon domain expertise from a long research career in meteorology, where he helped build a market-leading rainfall product. Based in Bellevue, WA, he shapes Obin AI’s technology and science direction while continuing to publish on GenAI, ML design patterns, and data engineering.
10 years of coding experience
25 years of employment as a software developer
Indian Institute of Technology Madras
Stackoverflow
3,986reputation
424kreached
164answers
18questions
google-bigquery
top-1%
sql
top-5%
tensorflow
top-5%
google-cloud-storage
top-5%
python
top-5%
google-cloud-platform
top-1%
Github Skills (49)
google-bigquery10
google-cloud-platform10
bigquery10
data-pipelines10
python10
evaluation10
gcloud10
data-science10
machine-learning10
bash10
image-annotation10
captions10
gcp10
data-preprocessing10
keras10
Programming languages (11)
Github contributions (5)
GoogleCloudPlatform/practical-ml-vision-book
Nov 2020 - Dec 2021
Role in this project:
ML Engineer
ML EngineerContributions:107 commits, 1 PR, 122 pushes in 1 year
Contributions summary:Valliappa implemented image captioning functionality by making changes to the 04_problem_types/04_image_captioning.ipynb notebook. The changes include taking out stop words and narrowing word selection during prediction. The user also created a notebook for labeling, and integrated the created dataset for use with a convolutional neural network. Further changes were made to a python script to convert jpeg files to TFRecord files, and the related shell scripts that use it.
GoogleCloudPlatform/ml-design-patterns
May 2020 - Apr 2021
Source code accompanying O'Reilly book: Machine Learning Design Patterns
Role in this project:ML Engineer
ML EngineerContributions:36 commits, 1 PR, 68 pushes in 11 months
Contributions summary:Valliappa contributed to a machine learning design patterns repository, primarily focusing on reproducibility and data representation. They implemented code changes to include tf transform working in an existing notebook, and created a notebook demonstrating text embeddings within BigQuery. Additionally, the user added a Python script for preprocessing and experimented with the integration of embeddings for data retrieval using the Keras autoencoder architecture.
machine-learning-bookmachine-learningpatternsdesign-patternso-reilly
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.