Researcher – Parallel Computing

Huawei Canada has an immediate 12-month contract opening for a Researcher.

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.

• Analyze the performance characteristics and scalability limitations of our current network gateway policy engine and explore parallel algorithms for rule lookup and incremental updates on GPUs and heterogeneous CPU/GPU or multi-core CPUs systems.
• Investigate hybrid CPU/GPU designs similar to high-speed DPI and pattern‑matching systems.
• Design and evaluate new data structures for network gateway rule matching.
• Implement solutions in C/C++ and optimize them to production‑quality standards (performance, robustness, and maintainability).
• Work closely with network gateway product and malware research teams to implement and integrate the new engine/solution into real products.
• Collaborate on patents and, where appropriate, academic or industry publications.
• Participate in other malware research projects as per job needs.

The target annual compensation (based on 2080 hours per year) ranges from $78,000 to $150,000 depending on education, experience and demonstrated expertise.

• Ph.D. (preferred) 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.

• Experience with two or more of the following:
  • Hybrid CPU/GPU systems (e.g., dynamic switching between CPU-only and hybrid modes), parallel computing, high performance computing
  • SIMT
  • AI Compiler
  • GPU programming in either (CUDA, HIP, OpenCL) or other accelerators
• Strong programming skills in C/C++ with experience writing performance‑efficient code.
• Good understanding of:
  • Algorithms and data structures
  • Computer architecture (caches, memory hierarchy, etc.)
• Having experience in the following is an asset:
  • Malware analysis/detection
  • Experience in LLM/GNN/ML with good understanding of the math fundamentals
  • TCP/IP Network stack