Research Engineer I
4 days ago
Nanyang Technological University's National Centre for Research in Digital Trust (DTC) is a research centre dedicated to executing a national program aimed at establishing Singapore as a strong trust hub.
The centre seeks to support efforts in creating a trusted digital environment for individuals and businesses through the digital transformation, providing assurance and confidence to both parties as they embrace digitalisation.
For more details, please visit
Job Description:We are seeking a highly skilled Research Engineer to collaborate with industry partners on AI Safety and Trust Technology projects, focusing on applying secure multi-party computation, homomorphic encryption, and federated learning in privacy-preserving machine learning.
The successful applicant should have in-depth knowledge of 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 demonstrate 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 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 overall competency in emerging areas of trust technologies.
- Engage global partners and researchers to understand the latest trends and advance Singapore's mindshare in this domain.
- 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 ability to explain complex technical concepts to both technical and non-technical audiences.
- Competent with strong analytical, problem-solving, and innovative thinking skills and 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.)
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