Senior Research Engineer — AI Data Security

Huawei Canada has an immediate permanent opening for a Senior Researcher.

The Digital Trust Lab is dedicated to ensuring user data flows while maintaining privacy. Researchers focus on key areas such as user identity authentication, data integrity, privacy protection, extensive model privacy assessment, multi-modal data identification, differential privacy, and federated learning. The lab supports deep research and encourages publications in leading journals. Research outcomes are applied across various Huawei product lines, including mobile phones, smart devices, and communications technologies.

• Participate to the advanced security research into threats, vulnerabilities, and defense mechanisms related to data infrastructure from endpoint devices to cloud services.
• Participate to the proposing, designing and prototyping of innovative data foundation security methods, including secure computation, access control, and cryptographic primitives.
• Producing insights of technology development in both academia and industry.
• Work closely with other research labs worldwide and product teams to optimize the solution and deliver concrete impact to real products.

• PhD Degree in Computer Science or Computer Engineering, or Master Degree with 4+ years experiences in related fields.
• Hands‑on expertise in building or securing data platforms (databases, data lakes, semantic indexes, ML data pipelines).
• Proven programming ability in C++/C, and proficiency in scripting languages such as Python and Bash.
• Good understanding of data security concepts: symmetric‑key cryptography (block ciphers, MAC, and authenticated encryption), public key cryptography (digital signatures, encryption, and key establishment), secure computation (secure multiparty computation, homomorphic encryption, zero‑knowledge proofs).
• Good understanding of system security concepts: access control (discretionary access control, mandatory access control, attribute‑based access control, dynamic access control), trusted execution environment (TEE).
• Experience with kernel development is an asset.
• Experience with cryptographic libraries (e.g. OpenSSL, GMP) is an asset.
• Experience with machine learning and deep learning is an asset.