Build workflows to ensure data extraction quality and storage into our backend data store
Architect, build and train ML / AI models that can predict outcomes and report on anomalies.
Design data pipelines to perform ETL on content / data from multiple types of source systems.
Create data analytics views using RDBMS / Key-Value stores, on private and public / cloud
Create software that is well tested, maintainable, extensible and scales out with large data Minimum Qualifications :
2+ years of software development with Python
2+ years of SQL (MySQL / Postgres) and Key-Value databases
1+ years of experience with scikit
2+ years of experience in data extraction, data transformation using custom Python / Java
Experience working with MapReduce / Hadoop / kafka / Elastic stack
Experience with Node backend and React / Redux
Experience working with git / mercurial, Amazon / Google cloud, Linux / LAMP stack
Experience in testing or test driven development
Experience with Data science and Machine Learning algorithm development
Highly competitive to match experience and capability Keep up-to-date through TVS
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Interested in Formal Verification
Then why not attend the TVS FormalVerification Bootcamp training
The 2-day Formal Verification Bootcamp is for design and verification engineers looking to enhance their knowledge of formal verification and to learn how to write effective assertions to find and fix bugs.
The course is a mix of presentations and hands-on development exercises.
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The TVS SystemC UVM library closely mimics UVM but gives users a license free UVM-based verification environment.
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