High-Performance Computing Engineer

1 week ago

Kanpur, Uttar Pradesh, India beBeeDeepLearning Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Lead Deep Learning Architect

We are seeking an experienced Lead Deep Learning Architect to design and implement groundbreaking GPU computers for demanding deep learning, high-performance computing, and computationally intensive workloads.

This role requires expertise in identifying architectural changes and/or completely new approaches for accelerating deep learning models.

The successful candidate will be responsible for converting business needs associated with AI-ML algorithms into a set of product goals covering workload scenarios, end-user expectations, compute infrastructure, and time of execution; this should lead to a plan for making the algorithms production ready.

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.

  • Design and implement ground-breaking GPU computers.
  • Identify architectural changes and/or completely new approaches for accelerating deep learning models.
  • Convert business needs associated with AI-ML algorithms into product goals.
  • Benchmark and optimize Computer Vision Algorithms and Hardware Accelerators.
  • Optimize algorithms for optimal performance on the GPU tensor cores.
Requirements
  • MS or PhD in Computer Science, Electrical Engineering, or related field.
  • Strong background in deployment of complex deep learning architectures.
  • 7+ years of relevant experience in at least a few of the following areas: Machine learning, 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): Numerical analysis, Performance analysis, Model compression and Optimization & Computer architecture.
  • Strong Data structures and Algorithms know-how with Excellent C/C++ programming skills.
  • Hands-on expertise with PyTorch, TensorRT, CuDNN.
  • Hand-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.
  • Excellent communication and collaboration skills.
  • Self-motivated and able to find creative practical solutions to problems.
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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