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Deep Learning Engineer - Parallel Computing

  • Job type: Contract
  • Location: Stuttgart
  • Salary: Competitive
  • Job reference: JB100034
  • Sector: Glocomms, Software Development & Architecture
  • Date posted: 12/04/2018
We are seeking a talented, self-motivated and self-directed software engineer to work on high performance solutions for Deep Learning.
You will be responsible for expanding and improving our Deep Learning capabilities to achieve best in class performance for training and prediction on single-core, multi-core, cluster, GPU, and multi-GPU systems. This is a challenging area that requires an understanding of machine learning, parallel algorithms, optimizing computation and data transfer, and designing simple but robust architectures for building complex Deep Learning models.
This position requires excellent object-oriented design and programming skills, strong inter-personal and communication skills, and significant software architecture experience. The team you will be joining is responsible for the architecture and performance of our Deep Learning tools as well as all aspects of GPU and multi-GPU support in Parallel Computing Toolbox.


  • Design and implement new systems for parallel and GPU processing of Deep Learning networks and layers
  • Design and implement wide-ranging performance optimizations
  • Work with other teams focused on Deep Learning, Parallel Computing, and Big Data
  • Design internal and customer visible APIs for GPU & parallel algorithms
  • Participate in all team activities such as planning, design discussions and reviews

Additional Qualifications

  • A relevant PhD or 3+ years equivalent experience working in a relevant industry
  • Excellent object-oriented design skills using MATLAB, Java or C++
  • Strong written and verbal communication skills
  • Experience working in MATLAB would be a significant benefit
  • Experience with GPU computing and performance optimization would be a significant benefit
  • Previous experience working with Deep Learning would be a significant benefit
please contact jag.bhabra (at) or call +44203 758 8902
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