Deepanshu Yadav is an AI Backend Engineer with 10 years of experience building and deploying machine learning systems across cloud and edge environments, holding a Master's in Data Engineering for AI. He has delivered production AI solutions at companies like Criteo, Dianomic, BEL and led a predictive maintenance system that boosted operations 4x while automating ML lifecycles on GCP. Skilled in TensorFlow, PyTorch, Prometheus/Grafana, and edge plugins (NumPy, pandas, scikit-learn), he blends SRE-minded observability work with model development and deployment. Notably, he helped integrate an underground vibration sensor into a homeland security PoC that secured an Indian Air Force contract, demonstrating his ability to translate research into operational impact. Now based in New Delhi, he is actively seeking immediate ML/AI engineering roles where he can move models from prototype to resilient production.
10 years of coding experience
3 years of employment as a software developer
Masters in data engineering, Information Technology, Masters in data engineering, Information Technology at Data ScienceTech Institute
Bachelor of Engineering (BE), Computer Engineering, Bachelor of Engineering (BE), Computer Engineering at Delhi Technological University
Contributions:2 commits, 2 pushes, 1 branch in 2 years 2 months
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