Hari Devanathan
Lead AI & Machine Leaning Engineer - Leidos QTC
Charlottesville, Virginia, United States
Summary
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Senior🎓
Top SchoolHari Devanathan is a Lead AI and Machine Learning Engineer with 12 years of experience building production ML and cloud-native systems for healthcare at Leidos, combining hands-on model development with infrastructure-as-code and MLOps. He has designed end-to-end pipelines—from OCR and high-throughput ingestion into OpenSearch to fine-tuning DistilRoBERTa on medical claim texts—and delivered solutions that materially improved accuracy and generated significant revenue. Comfortable across AWS, Terraform/Terragrunt, Docker/GPU training, and vector-search architectures, he also led multi-disciplinary teams to deploy LLM agents, synthetic data pipelines, and omnichannel conversational AI. A practical technical writer for TowardsDataScience and TealFeed, he translates complex ML concepts into tutorials and career advice for aspiring practitioners. Notably, he has a track record of squeezing dramatic performance and cost wins (e.g., reducing model build times and improving classification accuracy while scaling OCR and ingestion workflows).
12 years of coding experience
3 years of employment as a software developer
Master of Science - MS Analytics, Master of Science - MS Analytics at Georgia Institute of TechnologyBachelor of Science (BS) Computer Science, Bachelor of Science (BS) Computer Science at University of VirginiaProgramming languages (2)
Github contributions (5)
hd2zm/Data-Science-Projects
Feb 2019 - Aug 2022
Contributions:75 commits, 89 pushes, 1 branch in 3 years 6 months
hd2zm/hd2zm.github.io
May 2019 - Oct 2019
Contributions:1 PR, 36 pushes, 3 branches in 5 months
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