Data Scientist, Responsible AI (AI Practice), Toa Payoh

The Responsible AI team, part of GovTech's Artificial Intelligence Tech Practice, develops technical capabilities in defining, measuring, and mitigating various Responsible AI issues. We aim to be at the forefront of the AI safety and responsible AI space through learning, experimentation, and applied research.
Some of our past open-source work include RabakBench, KnowOrNot, MinorBench, and LionGuard, and you can find more details in our Responsible AI playbook ( huggingface page ( or the team blog ( (What we do)
Data scientists in the Responsible AI team will focus on experimenting with the latest developments in the Responsible AI space to raise the level of AI safety, robustness and fairness in government AI systems. This includes designing and conducting AI testing and evaluations for LLMs and agentic AI, finetuning models for alignment and red-teaming, and developing accurate and efficient guardrails. To do this well, we collaborate with many technical partners, including the private sector, academic institutions, and international players. We also aim to share our expertise with the wider community, so you will have the chance to contribute to open-source research, present our work and show how we are leading the way in Responsible AI. Additionally, we work closely with policymakers to provide technical guidance on AI governance and policies.
If you're curious about how Responsible AI, practical engineering, and real-world policy come together and would like to contribute your ideas and skills in this space, you'll find plenty of opportunities to learn, build, and make an impact with us. (What we are looking for) Demonstrated experience with end-to-end data science projects, from scoping, development, deployment, and monitoring Strong technical understanding of LLMs, especially how they work, how to do prompt engineering effectively, and how to build apps with them Good understanding of key AI safety, robustness and fairness concepts, especially in how to operationalise and apply them to AI systems Competent in Python programming, with some familiarity of cloud deployments for ML models and LLMs Strong interest in AI safety or responsible AI, especially given the need to read up independently on these areas and continuously explore and experiment Self-motivated, thinks proactively and creatively about how to solve challenges Desire to build tech for the public good We also have a strong preference for any applicant with informal or formal experience with any of the work below:
Conducting LLM or agentic AI safety testing, including jailbreaking or prompt injections Developing guardrails for LLMs or using equivalent tools (eg NeMo, LLM-Guard) Developing fairness assessments for AI systems GovTech is an equal opportunity employer committed to fostering an inclusive workplace that values diverse voices and perspectives, as we believe that diversity is the foundation to innovation. Our employee benefits are based on a total rewards approach, offering a holistic and market-competitive suite of perks. These include leave benefits to meet your work-life needs and employee wellness programmes. We champion flexible work arrangements (subject to your job role) and trust that you will manage your own time to deliver your best, wherever you are, and whatever works best for you. Learn more about life inside /GovTechCareers. Stay connected with us on social /ConnectWithGovTech.