JOB DESCRIPTION

Ecopia AI is an industry-leading AI company specializing in extracting insights from geospatial big data. Millions of geospatial images are captured every day by satellites, airplanes, vehicles, and personal devices – Ecopia converts this flood of pixels into high definition (HD) maps, leveraging AI to empower a wide range of applications such as smart cities, insurance, real estate, autonomous driving and augmented reality (AR). We are looking for talented self-starting engineers to join our platform team as High-Performance Computing Engineer.

Ecopia AI is located in the beautiful MaRS Discovery District building at 101 College Street in Toronto. Come join us in our mission to digitize the world with AI.

KEY RESPONSIBILITIES

  • Develop highly scalable and efficient computing infrastructure to support large scale training of deep neural networks to support high-performance processing of our PB-level geospatial data
  • Develop high-performance computing infrastructure to support computer vision applications like 3D reconstruction.
  • Work with algorithm team to design and develop our image recognizing / map creating neural networks
  • Develop efficient tools to deploy and schedule our tasks on large scale clusters.

KEY QUALIFICATIONS

  • BS or above in computer science or related fields
  • Deep understanding of computer architecture and parallel computing
  • Solid programming experience in C/C++. Familiar with Linux system and the related development tools.
  • Experience in parallel programming on Nvidia GPU or Intel x86 CPU.
  • Experience in deep learning and neural networks (familiar with Tensorflow / Pytorch / Caffe) is a plus.
  • Knowledge of computer vision is a plus.

COMMITMENT TO DIVERSITY AND INCLUSION

Ecopia Tech is committed to fostering a diverse and inclusive working environment. We welcome applications from qualified candidates of all backgrounds regardless of age, physical ability, gender, race, religion, and sexual orientation. We will provide any requested accommodation to candidates with disabilities throughout the recruitment process.

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