AI Safety & Security Research Scientist

Google Inc.; Singapore; On-site; SGD 180,000 - 280,000; Full time

Job summary

Google Inc. in Singapore is seeking a Research Scientist to advance threat mitigation for frontier AI and adversarial systems.

The role focuses on ML foundations for AI safety, robustness, interpretability, and continual learning, working with academic partners and global teams to shape next-generation trustworthy AI capabilities. You will develop new evaluation benchmarks, contribute to responsible AI research, and help translate theoretical ideas into robust production solutions across

Qualifications

• PhD in CS, related field, or equivalent practical experience.
• Experience in ML, adversarial ML or evaluating frontier AI systems (supervised/unsupervised/RL, interpretability, robustness, safety, generative models, agentic AI, multiobjective optimization).
• One or more scientific publication submissions to conferences, journals, or public repositories (e.g., CVPR, NeurIPS, ICML, ICLR).

Responsibilities

• Drive foundational ML research in model robustness, continual learning, and interpretability, and multiobjective optimization to advance trustworthy AI.
• Design and develop rigorous evaluation protocols, scenario-based benchmarks, and stress-testing methodologies for frontier AI capabilities and multi-agent consensus.
• Curate advanced datasets and conduct fine-tuning or optimization experiments to enhance model resilience against emerging threats and ensure safety constraints.
• Collaborate with regional engineering hubs, core product teams, and academic partners to transition proofs-of-concept into robust production solutions.
• Publish groundbreaking research in machine learning venues and engage with academic and industry research communities

Skills

Adversarial ML

Publications

ML research

Education

PhD in Computer Science

Tools

Python

Job description

Google Inc. in Singapore is seeking a Research Scientist to advance threat mitigation for frontier AI and adversarial systems.

The role focuses on ML foundations for AI safety, robustness, interpretability, and continual learning, working with academic partners and global teams to shape next-generation trustworthy AI capabilities. You will develop new evaluation benchmarks, contribute to responsible AI research, and help translate theoretical ideas into robust production solutions across