Big Data and Machine Learning Internals Developers- Ukraine

UA-Kiev
2 months ago
ID
2017-3917
Category
SW
Job Length
Full-Time

Overview

The Mellanox Bay Area based Big Data and Machine Learning R&D team is building cutting edge open-source integrated solutions for accelerating popular platforms such as: Apache Spark, Hadoop, TensorFlow, Caffe and more.

 

Mellanox’ ground breaking high-speed end-to-end networking solutions are a perfect match for today’s growing needs from distributed systems.

Those already proved themselves in many fields, such as: High Performance Computing, Cloud storage, Cloud compute clusters and many more. Many Big Data and Machine Learning frameworks do not take advantage of these advanced technologies, and our target is to introduce these powerful capabilities to popular frameworks and contribute the code to the open-source community.

 

Among Mellanox high-end networking capabilities are: 100Gb/s Ethernet and InfiniBand, RDMA (Remote Direct Memory Access), GPUDirect, SHArP (Scalable Hierarchical Aggregation and Reduction Protocol), FPGA accelerations and more.

Responsibilities

You will be trusted to:

  • Develop new solutions for network acceleration
  • Promote our design approaches in the relevant open source communities
  • Contribute code upstream
  • Design and automate highest quality testing facilities
  • Collaborate with design partners and customers for driving our solutions into production

Qualifications

You will need to have:

  • 4+ years of programming experience, of which 2+ years in Java or Scala
  • Experience with of one or more Big Data or Machine Learning platform, such as Apache Spark, Hadoop, TensorFlow, Caffe, etc.
  • Proven contributions to open-source communities
  • Highly technological out-of-the-box thinking

 

Nice to have:

  • Expert-level understanding of one or more Big Data or Machine Learning platform internals, such as Apache Spark, Hadoop, TensorFlow, Caffe, etc.
  • Proven contributions to open-source communities in these fields
  • Knowledge in cluster management frameworks
  • Experience with high performance networking technologies, such as RDMA

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