Research Engineer I

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.

We are looking for a Research Engineer to develop, implement, and oversee techniques and systems in Trust Technology and related areas such as privacy, security, and blockchain, which are important components of digital trust platforms. The role will focus on emerging technologies that engenders trust and espouse the values of fairness, safety, and privacy in digital technologies.

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 field
• Proficiency in Python is a must. Experience with other programming languages such as Java, C/C++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous.
• Proficiency in working with common Linux distributions (e.g., Ubuntu, CentOS) and familiarity with shell scripting and command-line tools.
• Experienced in developing and deploying machine learning models, with a focus on natural language processing (NLP) and large language models (LLMs). Skilled in data preprocessing, feature extraction, model training, and evaluation. Strong understanding of machine learning and deep learning techniques, including knowledge graphs, machine unlearning, and AI testing. Proficient with version control (e.g., Git) and collaborative tools. Expertise in end-to-end ML system development, covering data exploration, feature engineering, and model training/evaluation. Familiar with cloud platforms (AWS, GCP, Azure), containerization (Docker, Kubernetes), and best practices in software engineering.
• Interpersonal skill (e.g. Keen attention to detail and commitment to high-quality deliverables. understanding of ethical considerations and best practices in AI research, particularly concerning data privacy and security.)
• Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders, bridging the gap between research and practical application.
• Strong analytical and problem-solving skills, with a focus on developing innovative solutions for LLMs. Self-motivated and able to work independently, managing multiple tasks and projects in a fast-paced environment. Strong collaborative skills, with experience working in cross-functional teams.