Hursh Desai is a Software AI/ML Engineer based in Dallas with a decade of cross-disciplinary experience building and deploying machine learning products in cloud-native environments. Currently at GE HealthCare, he combines a strong foundation in QA and testing with hands-on expertise in TensorFlow, PyTorch, PySpark and MLOps tooling like DVC, Pachyderm, Docker, Kubernetes and Kubeflow to move models from prototype to production. His background spans academic research at Johns Hopkins, founding a rapid-response ncov19 initiative, and leadership roles in data science training—evidence of both technical depth and initiative-driven impact. He holds an MS in Computer Science from Johns Hopkins and complementary nanodegrees in deep learning and data science, reflecting a deliberate shift from biochemistry into scalable ML systems. Practical strengths include data wrangling, NLP, ETL and robust testing practices, enabling reliable, auditable ML pipelines. Colleagues describe him as an engineer who bridges research, infra and product needs while keeping deployments reproducible and testable.
10 years of coding experience
7 years of employment as a software developer
Nanodegree, Deep Learning / AI, Nanodegree, Deep Learning / AI at Udacity
Data Science, Data Science at Lambda School
Master of Science - MS, Computer Science, 4.0, Master of Science - MS, Computer Science, 4.0 at Johns Hopkins Whiting School of Engineering
Bachelor of Science - BS, Biochemistry and Molecular Biology, 3.5, Bachelor of Science - BS, Biochemistry and Molecular Biology, 3.5 at University of North Texas
Contributions:35 commits, 34 pushes, 1 branch in 3 months
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Hursh Desai - Software AI ML Engineer at GE HealthCare