Namratha Sreekanta
ML Engineering at Splunk
Fremont, California, United States
Summary
🤩
Rockstar🎓
Top SchoolNamratha Sreekanta is an ML engineer based in Fremont, California with about three years of focused industry experience building production-ready machine learning systems for security and NLP at Splunk. She applies deep learning to cybersecurity use cases—authoring a DGA detection notebook using pretrained models and developing a DSDL model to flag suspicious DNS TXT records—demonstrating a blend of research-driven modeling and pragmatic integration into detection pipelines. Earlier roles include data science work at Citrix and recommender-systems research at UC Santa Cruz, where she led user-acquisition experiments that introduced social diversity signals into e-commerce recommendations. Comfortable moving prototypes into operational settings, she pairs a strong academic foundation (M.S. in Technology and Information Management) with hands-on open-source contributions to a widely used Splunk security content repo.
3 years of coding experience
4 years of employment as a software developer
Bachelors of Engineering, Computer Science and Engineering, First Class with Distinction, Bachelors of Engineering, Computer Science and Engineering, First Class with Distinction at Visvesvaraya Technological UniversityUniversity of California Santa Cruz
Github Skills (10)
machine-learning10
deep-learning10
tensorflow10
python10
notebook9
detectors9
splunk9
cybersecurity9
mlops8
nlp7
Programming languages (1)
Github contributions (2)
splunk/security_content
Sep 2022 - Jan 2023
Splunk Security Content
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 29 commits, 6 PRs in 4 months
Contributions summary:Namratha's contributions center around the development and implementation of machine learning models within the Splunk security content repository. They created a notebook for DGA detection using a pretrained model, demonstrating expertise in utilizing deep learning techniques. Further contributions included the creation of a DSDL (Deep Splunk Data Language) model for detecting suspicious DNS TXT records. The user's work involves integrating machine learning models, specifically deep learning, into a cybersecurity context to enhance detection capabilities.
security-toolsdetectionsecuritycybersecuritysplunk
nsreekanta/hello_world
Sep 2022 - Sep 2022
Contributions:1 push in 1 day
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