Priya Kesarwani
Head Of Talent Acquisition & Product Development HR Tech at Nextedgesolution
New York City Metropolitan Area United States
Summary
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Rockstar🎓
Top SchoolPriya Kesarwani is a seasoned HR Tech leader with over 20 years of experience designing and delivering end-to-end talent acquisition strategies across IT and non-IT domains. As Head of Talent Acquisition & Product Development, she blends strategic HR leadership with hands-on product work to build AI-powered recruitment tools that cut time-to-hire while improving candidate quality. She has led workforce planning, employer branding, recruitment analytics and next-gen HR tool implementations, mentoring cross-functional teams to drive measurable hiring outcomes. Her background spans corporate and entrepreneurial environments, anchored by an MBA in HR and a track record of scaling recruitment operations. Less obvious: Priya also contributes technically, having worked on TensorFlow documentation and ResNet model improvements—bringing a rare combination of recruitment domain expertise and practical familiarity with machine learning tools. Based in the New York City metro area, she focuses on bridging talent strategy with technology innovation to optimize hiring at scale.
8 years of coding experience
9 years of employment as a software developer
b.sc., chemistry,zoology,botany, b.sc., chemistry,zoology,botany at Mahatma Jyotiba Phule (MJP) Rohilkhand UniversityMBA, HR, MBA, HR at Uttar Pradesh Technical UniversityH.S.C, XII, H.S.C, XII at U
Github Skills (8)
keras10
machine-learning10
deep-learning10
tensorflow10
resnet10
python10
documentation10
image-recognition8
Programming languages (4)
Github contributions (5)
tensorflow/models
May 2018 - Nov 2019
Models and examples built with TensorFlow
Role in this project:
ML Engineer
ML EngineerContributions:72 commits, 70 PRs, 100 pushes in 1 year 5 months
Contributions summary:Priya primarily contributed to the ResNet model implementation within the TensorFlow models repository, making performance improvements and integrating the Keras version of ResNet. They refactored and added Keras-based ResNet code, including model definition and training scripts. The user also addressed issues related to the input pipeline and added validation steps, highlighting their focus on optimization and integration of the Keras API.
deep-learningtensorflow
tensorflow/docs
Mar 2018 - Sep 2020
TensorFlow documentation
Role in this project:Back-end Developer & Technical Writer
Back-end Developer & Technical WriterContributions:18 commits, 3 comments in 2 years 7 months
Contributions summary:Priya primarily contributed to the documentation of TensorFlow's distribution strategy, focusing on explaining and demonstrating its usage. Their commits included the creation of guides and tutorials detailing how to distribute training across multiple devices and machines using various strategies like MirroredStrategy. The changes involved providing code examples for Keras and Estimator APIs, along with explanations of loss scaling and best practices for custom training loops.
deep-learningmachine-learningdeep-neural-networkstensorflow-tutorialstensorflow
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