Senior AI Engineer for High-Performance Computing Platforms

7 days ago

Salem, Tamil Nadu, India beBeeAI Full time US$ 1,50,000 - US$ 2,50,000

AI Systems Developer

At AIRA Matrix, we are building a cutting-edge platform for Life Sciences applications that leverage machine and deep learning techniques to develop diagnostic, prognostic, and predictive solutions. We improve efficiency, diagnostic accuracy, and turnaround times in pathology, microbiology, and ophthalmology workflows across pharmaceutical and healthcare laboratories.

The ideal candidate will have expertise in designing and implementing GPU computers that run demanding deep learning, high-performance computing, and computationally intensive workloads. Key responsibilities include identifying architectural changes and/or completely new approaches for accelerating our deep learning models, collaborating with various teams to drive an end-to-end workflow from data curation and training to performance optimization and deployment, and optimizing Computer Vision Algorithms and the Hardware Accelerators for performance and quality KPIs.

Requirements:

  • Master's or PhD in Computer Science, Electrical Engineering, or related field with a 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 (with focus on Deep Neural Networks), including understanding of DL fundamentals, adapting and training DNNs for various tasks, developing code for one or more of the DNN training frameworks, numerical analysis, performance analysis, model compression, and optimization & computer architecture.
  • Strong Data structures and Algorithms knowledge 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.
  • Excellent communication and collaboration skills.
  • Self-motivated and able to find creative practical solutions to problems.

Good to have:

  • 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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