Description:THE ROLE:The AI market is expanding rapidly, demanding higher I/O performance and complex system topology cases. Our DCGPU (Data Center GPU) products demand higher levels of quality and reliability in production.We are searching for a Data Science Engineer to help implement and drive our volume data strategy and integration into validation flows. This includes data collection and predictive modelling of quality metrics in manufacturing for high speed SerDes I/O like PCIe 5/6.THE PERSON:You will be a part of a team driving to improve client's product quality. You will be applying your Data Science and Automation experience to tackle challenging volume validation, manufacturing, and issue debug problems.KEY RESPONSIBILITIES:Implement automation and data strategy with validation technical leads and data architects to reduce time to market and time to qualityDevelop Python automation scripts for performance metrics data collection and characterizationDeliver robust data analytics solutions for visualization, results reporting, and building predictive statistical modelsDevelop database solutions to support storage and analysis of test results from validation and manufacturingIDEAL CANDIDATE:4 to 5 years’ experience in developing test automation solutions as an Automation EngineerExperience in developing high-availability, low-latency enterprise solutions as a Data Science/Engineering subject matter expertKnowledge of data modelling and data warehouse/lake best practices (SQL, Snowflake)Experience with data analytics, visualizations, and report generation (PowerBI, JMP)Experience building statistical predictive models factoring multiple sources of variation in chip and system manufacturingExperience writing performant code in Python, Java, Scala and good experience with SparkEnforcing and applying best practices for modular code development including 3rd party tool integrationExperience with SerDes PHY or High Speed I/O Validation at PCIeLinux power userACADEMIC CREDENTIALS:Bachelors or Master’s degree in Computer Engineering, Electrical Engineering, or Computer Science VIVA is an equal opportunity employer. All qualified applicants have an equal opportunity for placement, and all employees have an equal opportunity to develop on the job. This means that VIVA will not discriminate against any employee or qualified applicant on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status
Description:THE ROLE:The AI market is expanding rapidly, demanding higher I/O performance and complex system topology cases. Our DCGPU (Data Center GPU) products demand higher levels of quality and reliability in production.We are searching for a Data Science Engineer to help implement and drive our volume data strategy and integration into validation flows. This includes data collection and predictive modelling of quality metrics in manufacturing for high speed SerDes I/O like PCIe 5/6.THE PERSON:You will be a part of a team driving to improve client's product quality. You will be applying your Data Science and Automation experience to tackle challenging volume validation, manufacturing, and issue debug problems.KEY RESPONSIBILITIES:Implement automation and data strategy with validation technical leads and data architects to reduce time to market and time to qualityDevelop Python automation scripts for performance metrics data collection and characterizationDeliver robust data analytics solutions for visualization, results reporting, and building predictive statistical modelsDevelop database solutions to support storage and analysis of test results from validation and manufacturingIDEAL CANDIDATE:4 to 5 years’ experience in developing test automation solutions as an Automation EngineerExperience in developing high-availability, low-latency enterprise solutions as a Data Science/Engineering subject matter expertKnowledge of data modelling and data warehouse/lake best practices (SQL, Snowflake)Experience with data analytics, visualizations, and report generation (PowerBI, JMP)Experience building statistical predictive models factoring multiple sources of variation in chip and system manufacturingExperience writing performant code in Python, Java, Scala and good experience with SparkEnforcing and applying best practices for modular code development including 3rd party tool integrationExperience with SerDes PHY or High Speed I/O Validation at PCIeLinux power userACADEMIC CREDENTIALS:Bachelors or Master’s degree in Computer Engineering, Electrical Engineering, or Computer Science
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