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Job content

  • Responsibilities:
    • Implement advances available in Parallel Computing, Artificial Intelligence and Machine Learning as custom programs on multicore CPUs and GPUs
    • Build ‘Proof of Concept’ (PoC) applications using suitable technologies
    • Collaborate, research, and publish findings at various internal and external forums
    • Interface with Siemens internal customers and provide Parallel Computing/AI/ML based solutions for their needs
  • Technical Expertise
    • An ideal candidate will have keen interest and solid skills in high performance parallel computing on multicore CPUs and GPUs with background in implementation of deep learning algorithms/frameworks. Intuition and ability to develop deep/machine learning algorithms will be a big plus.
    • Excellent programming skills in C/C++/CUDA/OpenCL/Python are essential.
    • Experience in implementing deep neural networks using TensorRT, TensorFlow, OpenVINO, Caffe.
    • Exposure to CuDNN/CuBLAS and good understanding of linear algebra operations is a big plus.
    • Prior experience in parallelization technologies such as pthreads, OpenMP, MPI is highly desirable.
    • Experience with performance optimization and profiling/tracing tools such as gprof, Intel VTune, Pin, PAPI, JetBrains is a big plus.
    • Domain experience in any of the following will be a big plus: Image and Signal Processing, Scientific computation, Edge computing, Simulation.
  • Qualifications
    • Bachelors/ Masters/ Ph.D. in Computer Science/Electrical/Electronics and Communication
    • Demonstrated relevant work experience of 1 – 3 years
    • Technical papers at prestigious conferences and journals
  • Additional requirements:
    • Excellent communication skills in English
    • Self-motivated and independent, but also comfortable with team-work.
    • International R&D exposure will be a plus
    • Focus on quality and result orientation
    • Optimistic, can-do attitude


Organization:
Technology

Company: Siemens Technology and Services Private Limited

Experience Level: Early Professional

Job Type: Full-time

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Deadline: 20-06-2024

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