Rohit Singh
Team Lead Customer Focus Team Korea Japan at Nearfield Instruments
Bengaluru, Karnataka, Netherlands
Summary
👤
Senior🎓
Top SchoolRohit Singh is a product-focused engineering leader with nine years of experience driving adoption of advanced semiconductor metrology solutions across global fabs, currently leading the Customer Focus Team for Korea and Japan at Nearfield Instruments. He combines deep technical expertise in AFM, HVSEM and e-beam metrology with product marketing skills—translating complex tool capabilities into Market Requirement Specifications, Red Team analyses, and go-to-market strategies that accelerate NPI adoption with customers like Samsung and SK Hynix. Rohit pairs this domain knowledge with hands-on ML engineering experience—contributing GPU-focused training optimizations to the widely used ZenML project—bringing a pragmatic data-science lens to instrumentation and process yield improvement. Trained as an integrated B.Tech/M.Tech metallurgical engineer from IIT (BHU), he’s comfortable bridging engineering, applications, and customers to find high-impact opportunities across advanced nodes while continually exploring new tools and methods.
9 years of coding experience
6 years of employment as a software developer
B.Tech+M.Tech, Integrated Dual Degree (IDD), Metallurgical Engineering, B.Tech+M.Tech, Integrated Dual Degree (IDD), Metallurgical Engineering at Indian Institute of Technology (Banaras Hindu University), Varanasi
English, Hindi
Github Skills (14)
pytorch10
machine-learning10
mlops10
gpu10
python9
deeplearning-ai9
deep-learning9
workflow-engine8
ai8
developer-tools6
devops6
devtools6
data-science5
tensorflow4
Programming languages (6)
Github contributions (5)
zenml-io/zenml
Jun 2021 - Jun 2021
ZenML 🙏: The bridge between ML and Ops. https://zenml.io.
Role in this project:
ML Engineer
ML EngineerContributions:8 reviews, 5 commits, 1 PR in 10 days
Contributions summary:Rohit primarily focused on modifying and optimizing PyTorch trainer components within the ZenML project. They made significant changes to the `FeedForwardTrainer`, including moving batches to the appropriate device, refactoring the device assignment logic, and modifying the model output handling. Their contributions involved adapting the code for GPU utilization, and ensuring data is correctly processed for the neural network model. These changes suggest a focus on improving the training and testing processes within the ML pipeline.
devops-toolspythonproduction-readytensorflowproduction
SKRohit/Generating_Text_Summary_With_GPT2
Dec 2019 - Jan 2023
A simple approach to use GPT2-medium (345M) for generating high quality text summaries with minimal training.
Contributions:21 commits, 20 pushes, 1 branch in 3 years 1 month
nlpnatural-language-generationapproachtraininghigh-quality
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