Machine Learning Researcher
- 7101 Av du Parc, Montréal, QC H3N 1X9, Canada
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.
“Huawei will continue to be an important contributor to Canada’s knowledge-based economy,” “Openness and diversity are Canada’s great strengths. They help attract global talent and business. Huawei Canada’s R&D spending creates jobs, trains talents, supports fundamental research, and accelerates knowledge-to-impact in Canada. We are proud of all of that.”
Changtian Cai, President, Huawei Canada R&D.
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.
Work on innovative ML models with applications on graph-structured data (such as telecommunication networks, recommender systems, and knowledge graph);
Keeping up-to-date on selected areas of ML (such as graph representation learning, recommended systems, and deep learning);
Implement algorithms for proposed models and applications;
Work closely with researchers in the team;
Write scientific reports;
Submit manuscripts to top-tier conferences and file high-value patents.
Master’s or PhD degree in Computer Science, Statistics, Applied Mathematics or a related technical field;
Good understanding of basic ML methods (supervised/unsupervised learning);
Good knowledge of Deep Learning (DL) components (training, regularization, generalization) and familiar with common DL architectures (e.g., CNNs, RNNs, AEs, GANs);
Have publication experience in top AI/ML conferences are preferred (e.g. NeurlPS, ICML, KDD, ICLR and etc.);
Knowledge in graph representation learning models (e.g., Deepwalk, GCNs, and GraphSAGE);
Experience in telecommunication system such as wireless networks is a plus;
Experience in language modeling, knowledge graph or recommender systems is a plus;
Experience in parallel model training is a big plus;
Strong coding skills in Python;
Experience with coding in Tensorflow or Pytorch;
Have good communication skills.