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Deep Learning Researcher
2 months ago
We are seeking a highly skilled Deep Learning Researcher to join our team at Huawei Technologies Canada Co., Ltd. as a 12-month contract position.
The successful candidate will design optimized algorithms and models for hardware accelerators, stay updated with recent advances in the field by reading academic papers, and collaborate closely with researchers to provide solutions to engineers.
- Design, implement, and integrate models and algorithms for deep learning applications on hardware accelerators.
- Evaluate, analyze, and derive insights from experimental data to improve model performance and efficiency.
- Publish scientific papers on research findings and contribute to the development of the field.
To be successful in this role, you will need:
- A Master's or Ph.D. in Computer Science, Computer Engineering, or a related field.
- Proven experience with deep learning models, which can be demonstrated through work experience, internships, or projects.
- Proficiency in deep learning frameworks such as PyTorch and TensorFlow.
- Excellent communication skills, self-motivation, creativity, and strong attention to detail.
- Strong software development skills in Python or C++.
- Hands-on experience and comprehensive knowledge of at least one deep learning architecture, such as Transformers, Graph Neural Networks (GNN), Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), Long Short-Term Memory (LSTM), or Variational Autoencoders (VAE).
- Experience in one of the following areas: Software-Hardware or Algorithm-Hardware Co-Design, Search Techniques: Bayesian Optimization, Evolutionary Algorithms, or Reinforcement Learning.
We offer a competitive salary range of $120,000 - $180,000 per year, depending on experience.
In addition to a challenging and rewarding work environment, we also offer a comprehensive benefits package, including medical, dental, and vision coverage, as well as a generous retirement plan.
Relocation assistance may be available for candidates who are not currently based in Canada.