We are looking for world class software engineers with deep experience in large scale data processing systems and machine learning. You will have a passion to push the limits of distributed computing frameworks to get every ounce of performance out of them. You will use and contribute to existing frameworks like Spark,Flink,Storm etc and also blaze the trail on innovations in this space. You will be excited by the prospect of working collaboratively with other groups internal to Apple and also the open source community. You will help build a world class control plane for provisioning and lifecycle management of large scale data processing clusters. This position offers a competitive salary and benefits.
- Committers/Contributors to Apache Spark,Flink,Storm,hadoop strongly preferred.
- Deep understanding of Apache Spark including project tungsten and catalyst optimiser.
- Experience with development and maintenance of large scale Spark jobs.
- Experience with design and development of data connectors from Spark.
- Good Understanding of Columnar database design and implementation.
- Experience with Scala strongly recommended.
- Deep understanding of core CS including data structures, algorithms and concurrent programming
- Strong background in systems level Java including garbage collection, concurrency models, native and async IO, off heap memory management etc.
- Passion for developing and testing clear, robust code
- Sound knowledge of UNIX and shell scripting
- Experience with virtualization and containerization
- Great communication skills
The candidate will be able to demonstrate a strong practical understanding of how to develop practical, fault-tolerant high-performance distributed systems. Applicants will have extensive experience in industry or research developing robust, server-side Java, Scala or C++ code and will be able to demonstrate creativity, initiative and the ability to work to deadlines. We are looking for a great team player with the ability to communicate technical concepts effectively to others.
BS or MS in CS or equivalent
This position will close on April 27, 2018.