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|Job Title:||Sr Staff CPU Performance Architect - Cloud Storage and Big Data|
|Perm or Contract:||Permanent|
|Location:||Santa Clara, CA|
|Skills:||ARM, data mining algorithms, ARM, Decision trees, big data and storage source, Apache Spark, Hadoop, Cassandra|
|Job Description:|| As part of our Performance Engineering group, youíll help craft solutions that deliver high performance on ARM servers. Youíll work across disciplines to transform define, implement, analyze and optimize solutions.|
The performance engineering group works across HW, FW, OS, tools and applications to identify trends, mine data, and help Marvell improve quality and performance of solutions based on ARM servers.
This position requires thorough understanding of open source big data and storage source bases such as hadoop, spark, cassandra etc, as well as deployment models. Defining as well as working with customers on use cases, designing appropriate solutions, analyzing performance against competitive solutions and optimizing the solution from the application all the way to the HW.
Bachelorís degree in Computer Science, Electrical Engineering or related fields and 10- 15 years of related professional experience OR Masterís degree and/or PhD in Computer Science, Electrical Engineering or related fields with 5-10 years of experience.
5-10 years as data scientist or database engineer
Solid competency in statistics, working knowledge of data mining algorithms including decision trees, probability networks, association rules, clustering and regression
Solid analysis and design skills to facilitate creative insight to solution analysis
Strong experience with Apache Spark, Hadoop, Cassandra or other big data technologies.
Self-starter with entrepreneurial experience and ability to interact with other disciplines
Proven Creativity to go beyond current tools to deliver best solution to the problem
Strong programming skills in Python, or similar language Preferred
Data Engineering or Data Mining experience with cloud deployment
Experience with open source participation
Experience with ARM architecture porting or optimization
Kernel/Driver level experience
Solid understanding of modern processors
Passion for performance analysis and optimization