$320,000 - 488,750 yearly
Number of Applicants
:000+
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NVIDIA is seeking a Distinguished Engineer for the Apache Spark Acceleration group.
Over the past five years GPU accelerated data processing has moved from proof of concept to production deployments. Many enterprises are now recognizing the needs of accelerated computing for large scale data processing. Multi-node GPU deployments will reduce cloud computing costs and lower latency of large scale data processing.
At NVIDIA, we have been invested in accelerating Apache Spark, providing an open source plugin for Apache Spark. Apache Spark is the most popular data processing engine in data centers. We strive to accelerate Spark applications on GPUs without any code changes. Our OSS RAPIDS Spark library is integrated with on-premise and cloud services such as AWS EMR, Databricks, Google Dataproc, Oracle Cloud Data Flow, Bytedance Volcengine, Tencent Cloud and Cloudera.
You will serve as a hands-on architect of Nvidia Spark Acceleration Group. You will work with a team of distributed system engineers including PMC and Committers of Apache Spark, Apache Hadoop, Apache Hive, and Apache Arrow. You will engage in open source projects such as Apache Spark, RAPIDS, Apache Iceberg, Delta Lake, UCX and more.
Excellent programming skills in C++, Java, and/or Scala
Able to work with teams across boundaries and geographies
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.#deeplearningAuto-Apply to Distinguished Engineer Jobs with your AI JobCopilot
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