Research Engineer (Ai Model Evaluation), Ihpc

Agency for Science, Technology and Research – Queenstown

The Centre for Advanced Technologies in Online Safety (CATOS; ) was established in

• to host Singapore's Online Trust and Safety (OTS) Programme, a national research programme that leads the advancement of whole-of-nation technology capabilities to monitor and tackle online harms.

The Systems Engineering Pillar of CATOS focuses on translational research and development, including evaluating, testing and integrating research output into needle-moving applications.

One of the major outcomes will be a technological platform with an integrated suite of deep tech OTS engines, which analyses various internet sites and platforms for fast-trending harmful online content, such as non-factual claims, deepfakes, and hateful and toxic content.

Different combinations of OTS engines can then be integrated and adapted to address the specific requirements of various stakeholders.

This role will be responsible for systematically evaluating AI models and datasets to understand the strengths and weaknesses of existing tools in this field and identify ways to adapt promising tools to their intended applications.

The work will create valuable knowledge to inform end-users and technology researchers, helping to ensure that the technologies from CATOS and its partners are of desirable performance and robustness for the intended use cases and applications.

The candidate will assume the following roles and responsibilities :

As a Research Engineer, contribute to the evaluation of emerging technologies and data underneath the technologies.

Collaborate with senior team members, stakeholders and cross-functional teams to incorporate requirements that arise from the evolving landscape.

Contribute to key CATOS events that are aimed at engaging the research, industry, government agencies, NGOs and the general public

JOB REQUIREMENT :

BA / BS / Master degree in Computer Science / Information Technology / Computer Engineering / Information Systems / Data Engineering / Computational Social Science or equivalent.

Demonstratable experience in using machine learning / deep learning frameworks and models.

Proficient with programming languages (e.g., Python, Java, C / C++, MATLAB) and tools.

(e.g., Jupyter Notebook, VS Code)

Ability to quickly develop and iterate on prototypes.

Experience in using (Multi-Modal) Large Language Models is valued.

Good communication and interpersonal skills for working in a multicultural work environment.

Candidates with no experience may apply.

Our research and engineering work is highly interdisciplinary, agile, and pragmatic in nature.

We expect everyone to take ownership of their role, responsibilities, and tasks.

We encourage everyone to speak up when they have feedback or ideas for improvement.

We provide honest feedback to one another, which can be tough at times, but it fosters rapid learning.

We care about each other's professional growth and well-being.

When applying, please share at least two representative research projects or publications that you have developed independently or contributed to significantly.

Please note that only shortlisted candidates will be notified.

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