GPU Computing Strategist

3 days ago

Bareilly, Uttar Pradesh, India beBeeLeader Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
GPU Computing Leader

We seek a visionary leader to spearhead the design and implementation of cutting-edge GPU computers that can efficiently handle demanding deep learning, high-performance computing, and computationally intensive workloads.

  • Provide strategic direction in designing and implementing groundbreaking GPU computers.
  • Identify architectural changes and/or completely new approaches for accelerating our deep learning models.
  • Help us address strategic challenges including compute, networking, and storage design for large-scale, high-performance workloads.
  • Translate business needs associated with AI-ML algorithms into product goals covering workload scenarios, end-user expectations, compute infrastructure, and time of execution.
  • Benchmark and optimize Computer Vision Algorithms and Hardware Accelerators for performance and quality KPIs.
  • Optimize algorithms for optimal performance on the GPU tensor cores.
  • Collaborate with various teams to drive an end-to-end workflow from data curation and training to performance optimization and deployment.
  • Assign tasks to the team and monitor progress.

Key Requirements:

  • MS or PhD in Computer Science, Electrical Engineering, or related field.
  • 7+ years of relevant experience in Machine learning (with focus on Deep Neural Networks), including understanding of DL fundamentals; Experience adapting and training DNNs for various tasks; Experience developing code for one or more of the DNN training frameworks (such as Caffe, TensorFlow or Torch).
  • Strong Data structures and Algorithms know-how with Excellent C/C++ programming skills.
  • Hands-on expertise with PyTorch, TensorRT, CuDNN.
  • Hands-on expertise with GPU computing (CUDA, OpenCL, OpenACC) and HPC (MPI, OpenMP).
  • In-depth understanding of container technologies like Docker, Singularity, Shifter, Charliecloud.
  • Proficient in Python programming and bash scripting.
  • Proficient in Windows, Ubuntu, and Centos operating systems.

Desirable Skills:

  • Hands-on experience with HPC cluster job schedulers such as Kubernetes, SLURM, LSF.
  • Familiarity with cloud computing architectures.
  • Hands-on experience with Software Defined Networking and HPC cluster networking.
  • Working knowledge of cluster configuration management tools such as Ansible, Puppet, Salt.
  • Understanding of fast, distributed storage systems and Linux file systems for HPC workloads.

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