Satyendra Kumar

Senior machine learning operations engineer at Matterworks

Satyendra Kumar has a wealth of experience in the field of machine learning operations engineering. Satyendra began their career in 2003 as a Software Engineer at InterGlobe Technologies, where they worked on the AirDeccan.NET Project. In 2006, they joined Interra Information Technologies (InterraIT) as a Team Lead. Satyendra then moved to MasterBrand Cabinets as a Sr. Solution Lead in 2008. In 2012, they joined Littelfuse as a Sr. Enterprise Architect ML, where they led the e-commerce search & personalization transformations using BERT Machine learning algorithm. Satyendra also designed and led the team to build MLOps platform using GCP Kubernetes, Kubeflow pipelines & Airflow to scale the ML models training, validations, deployment & monitoring. In 2022, they joined Matterworks as a Senior Machine Learning Operations Engineer, where they are building a distributed deep learning platform to enable real-time insights into cellular biology to accelerate therapeutic research, development, and manufacturing for metabolomics.

Satyendra Kumar's education history includes completing a Bachelor of Commerce, Mathematics, and Economics from Delhi University from 1997-2000, a Post Graduate Diploma in Computer Applications from Jamia Hamdard from 2001-2003, an Advance Diploma in Computer Science from the Center for Development of Advance Computing from 2002-2003, and a Master of Computer Applications (MCA) from Sikkim Manipal Institute of Technology - SMU from 2005-2007. Additionally, they have completed class X from St. Michael's High School from 1995-1997 and class XII from Loyola High School from 1989-1995. Satyendra also holds two certifications: AWS Certified Solutions Architect - Associate from Amazon Web Services obtained in March 2018, and Software AG Certified webMethods Integration Associate from Software AG obtained in July 2021.

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Glenview, United States

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Matterworks

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Matterworks is enabling scalable metabolomics through AI and analytical chemistry to accelerate therapeutic research, development, and manufacturing.


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11-50

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