Nanyang Technological University's National Centre for Research in Digital Trust (DTC) is a Trust Technology Research Centre to execute a national program to help put Singapore into a strong trust hub. The key objective is to support efforts to create a trusted digital environment for people and businesses in the digital transformation by providing businesses and consumers with greater assurance and confidence as they digitalize.

For more details, please view https://www.ntu.edu.sg/dtc

We are looking for a Research Engineer to be involved in research and development collaboration with industry, on AI Safety and Trust Technology, especially on the topic of applying secure multi-party computation, homomorphic encryption, and federated learning in privacy-preserving machine learning. The successful applicant is expected to be familiar with fully homomorphic encryption and its applications in AI models.

Key Responsibilities:

• Conduct research into trust technologies testing - translating algorithms, tools, and frameworks into working prototypes that can explain how research outputs can be productised into new capabilities.
• Work closely with Centre's researchers to design and develop system implementation work from research into the product.
• Design and build working tools that can support the technology transfer of new capabilities to research partners and can be used to showcase the value of a given research outcome.
• Write and maintain technical documentation, presentations, and papers on research into trust technologies testing, helping to educate and raise the overall competency in emerging areas of trust technologies.
• Engage global partners and researchers to understand latest trends and advance Singapore's mindshare in this domain.

Job Requirements:

• Bachelor's degree in computer science/ engineering or related fields.
• Proficiency in C/C++, Python and machine learning framework such as PyTorch/TensorFlow are essential. Proficient with Linux (e.g., Ubuntu, CentOS) and shell scripting.
• Strong knowledge of machine learning and deep learning techniques (e.g., CNN and tree-based ML models). Cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) experience required. Experience with Secure Multi-Party Computation (SMPC), Homomorphic Encryption (HE) and Federated Learning (FL) is a plus.
• Familiarity with Git and collaborative development tools with experience in end-to-end ML system development (data exploration, feature engineering, model training/evaluation) is advantageous. Solid understanding of software engineering principles and best practices and the ability to explain complex technical concepts to both technical and non-technical audiences.
• Competent with strong analytical, problem-solving, and innovative thinking skills and a good understanding of ethical AI practices, especially related to data privacy and security.
• Interpersonal skill (e.g. Self-motivated, able to work independently in a fast-paced environment with strong collaboration skills. Experience working in cross-functional teams with attention to detail and commitment to delivering high-quality results.)

We regret to inform that only shortlisted candidates will be notified.