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You will work with the open source community to accelerate Apache Spark with GPUs for data science. Apache Spark is the most popular data processing engine in data centers. We strive to significantly accelerate Apache Spark 3.x use cases without application code changes. You will work on open source libraries (such as) to be used in both on-premises and cloud services (such as Databricks, AWS EMR, Google Dataproc, and Cloudera).
What you'll be doing:
Leading the design and implementation of accelerated Apache Spark and related big-data frameworks
Creating a collection of accelerated libraries for data analytics and machine learning
Working with a team of outstanding engineers including PMC and Committers of Apache Spark, Apache Hadoop, Apache Hive, and Apache Arrow
Engaging open source communities (including Apache Spark, RAPIDS and UCX) for technical discussion and contribution
Working with NVIDIA strategic partners on deploying advanced machine learning and data analytics solutions in public cloud or on-premise clusters
Presenting technical solutions in industry conferences and meetups
Provide recommendations and feedback to teams regarding decisions surrounding topics such as infrastructure, continuous integration and testing strategy
Build, test and optimize CUDA/C++ libraries across different platforms
What we need to see:
BS, MS, or PhD in Computer Science, Computer Engineering, or closely related field or equivalent experience
15+ years of work experience in software development
5+ years working experience with key open source big-data projects as a contributor or committer including Apache Spark, Apache Flink, Trino, Apache Kafka, Apache Hive, Apache Arrow, Apache Hadoop, Delta Lake, Apache Iceberg
Outstanding technical skills in designing and implementing high-quality distributed systems
Excellent programming skills in C++, Java, and/or Scala
Ability to work successfully with multi-functional teams across organizational boundaries and geographies
Highly motivated with strong interpersonal skills
You will also be eligible for equity and .
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