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Job description
Huawei Canada has an immediate permanent opening for a Researcher.
About the team:
The AnShi Lab focuses on developing next-generation gateway software architecture by prioritizing file security and software innovation. The focus is on conducting mid- and long-term research to create high-value patents and guide datacom gateway development. The goal is to establish industry benchmarks through cloud-based, intelligent software engineering. By leveraging local resources and fostering talent, we aim to build a high-performance technical expert team, improving both organizational vitality and personnel capabilities.
About the job
Partner with malware analysts and security stakeholders to define problem scope, labeling strategy, and evaluation methodology.
Conduct industry/academic research and produce concise surveys and technical reports.
Design and implement LLM/GNN/ML approaches for malware/threat classification (e.g., family/behavior classification, malicious vs. benign).
Build scalable data pipelines for ingestion, preprocessing, deduplication, and dataset management.
Drive experimentation end-to-end: model training, calibration, benchmarking, error analysis, and iteration.
Contribute to patents/publications; (Optional) travel/conferences.
The total target annual compensation for this position ranges from $106,000 to $156,000 depending on education, experience and demonstrated expertise.
About the ideal candidate
Ph.D or Masters degree in Computer Science, Electrical & Computer Engineering, Mathematics, or a closely related field, with a focus on systems, high-performance computing, or databases, or equivalent research experience.
Very strong foundation in LLM/AI/ML with solid mathematical understanding (Transformers, representation learning, optimization, evaluation).
Strong programming and engineering skills (Python; deep learning frameworks such as PyTorch/JAX; reproducible experimentation).
Excellent teamwork and cross-cultural communication; fluent English (written and spoken).
Malware analysis / reverse engineering experience; cybersecurity analysis background.
Big data processing experience (Spark/Ray, distributed ETL).
Knowledge of compilers (e.g., LLVM), operating systems, and low-level programming (C/C++ / embedded C).