AI Researcher
Edmonton, AB, Canada
Huawei Technologies Canada Co., Ltd.
Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices.Company Description
About Huawei
With 194,000 employees and operating in more than 170 countries and regions, Huawei is a leading global creator and provider of information and communications technology (ICT) infrastructure and smart devices. Integrated solutions span across four key domains – telecom networks, IT, smart devices, and cloud services. Huawei is committed to bringing digital to every person, home and organization for a fully connected, intelligent world.
About Huawei Canada
Huawei Canada focuses on fundamental research and development aimed at solving complex technical problems in emerging technologies like 5G, AI, Human Computer Interaction and Autonomous Driving. With ongoing research initiatives with 10 Universities across Canada and strategic collaboration agreements with several Universities, we support Canada’s rich research community. In 2020, Huawei Canada ranked among the Top 20 corporate R&D investors in the country with a huge 40% increase in R&D investment year over year. Huawei Canada was established in 2008 and now has a total workforce of 1,200 in our six research centers across Canada.
Why work with Huawei Canada?
You will have the opportunity to work on real world problems that impact people across the globe. Many of our researchers are actively involved in publishing conference and journal papers, inventing patents and solving challenging technical problems. With cutting edge tools, access to highly specialized leaders and researchers, and significant funding, you will be well supported to fulfil your potential and pursue your professional dreams.
Job Description
Responsibilities (work scope may include one or multiple of the following aspects):
- Build optimized neural networks and deep learning SW/HW for computer vision and natural language processing tasks.
- Work on advanced deep learning optimization techniques and AutoML techniques, including Neural Architecture Search, hyperparameter optimization, meta-learning, data engineering, model compression/pruning, etc.
- Work on AI accelerator design for DNN, including hardware architecture optimization, the software library and tensor implementation optimization, and deep learning compiler for GPU/NPU/TPU/CPU.
- Develop heuristic search and Reinforcement Learning techniques for practical large-design space exploration, frequently in conjunction with Bayesian Optimization, gradient-based and statistical learning methods, hyperparameter optimization, monte carlo tree search, etc.
- Apply machine learning, graph learning, statistical learning to neural network design and SW/HW co-design for deep learning.
General expectations:
- Read academic papers and keep up-to-date with the latest advances in related fields
- Propose solutions and develop prototypes on open-source and internal benchmarks
- Deploy research results on customized internal hardware platforms, including mobile AI chips.
- Provide solutions for engineers and product teams to achieve technology transfer
- Coauthor and publish research papers in top conferences
Qualifications
- Ph.D. in computer science, computer engineering, or related fields
- Familiarity with popular deep learning architectures in computer vision, NLP, etc.
- Excellent communication skills, self-motivated, with creative thinking and attention to details
- Strong software development skills
Preferred Qualifications:
- Specialization in deep learning, machine learning, reinforcement learning, or ML systems in general.
- Publications in top-tier conferences
Tags: Architecture Autonomous Driving Bayesian Computer Science Computer Vision Deep Learning Engineering GPU Machine Learning Monte Carlo NLP R R&D Research Statistics
Perks/benefits: Conferences
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