Advanced Deep Learning Systems Developer

7 days ago


Tiruchi, Tamil Nadu, India beBeeEngineer Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Description

We are seeking a visionary leader to spearhead the development and implementation of groundbreaking GPU computers that run demanding deep learning, high-performance computing, and computationally intensive workloads.

The ideal candidate will have expertise in identifying architectural changes and/or completely new approaches for accelerating our deep learning models. They will also help us with strategic challenges such as compute, networking, and storage design for large-scale, high-performance workloads, effective resource utilization in a heterogeneous computing environment, evolving our private/public cloud strategy, capacity modeling, and growth planning across our products and services.

As an architect, you 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.

You will also be responsible for benchmarking and optimizing Computer Vision Algorithms and Hardware Accelerators for performance and quality KPIs. Additionally, you will optimize algorithms for optimal performance on the GPU tensor cores.

Collaboration with various teams is essential to drive an end-to-end workflow from data curation and training to performance optimization and deployment. You will assign tasks to the team and monitor their progress.

  • Strong background in deploying complex deep learning architectures
  • 7+ years of experience in Machine Learning, including understanding of Deep Neural Networks, adapting and training DNNs for various tasks, and developing code for one or more DNN training frameworks (such as Caffe, TensorFlow, or Torch)
  • Excellent C/C++ programming skills and 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 include:

  • 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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