AI Safety Research Scientist (ML Research)
Oct 20, 2023
Research Roles (AI Governance and AI Safety)
An AI Safety Research Scientist working within ML works on developing methodologies and strategies to ensure the safety, controllability, value alignment, and robustness of AI systems. They often conduct in-depth research and formulate new ideas in machine learning or work on improving existing ones, an endeavor which usually involves mixes of algorithms design, theory, programming, a security mindset, and ML engineering. An AI Safety Research Scientist helps establish and/or execute the research trajectory to enhance the safety, alignment, and resilience of AI systems against adversarial or malicious applications, as well as against accidental rogue actions and broader sociotechnical systemic failures. Note that this job sometimes overlaps with the role of AI Safety Research Engineer, since that job partially consists in implementing the findings from AI safety research scientists.
Define paths for research objectives and tactics aimed at enhancing the safety, alignment, ethics, and resilience of AI systems.
Engage in cutting-edge research concerning AI safety subjects like Reinforcement Learning from Human Feedback (RLHF), adversarial training, cotraining, AI-assisted alignment research, mechanistic interpretability, more novel techniques, as well as robustness and related areas.
Facilitate collaboration among diverse teams, such as the tech team, legal, policy, and other research teams.
Think of methods to assess the safety of current systems and then put those plans into action by conducting practical tests and specifying benchmarks.
Take a proactive role in conducting safety evaluations on AI/ML models and systems, ideating neglected weaknesses and malign capabilities, pinpointing areas of potential hazard, and suggesting mitigation strategies.
Why we think this job is impactful
AI safety research scientists are instrumental in guiding responsible AI development and preventing catastrophic risks as they help to identify, understand, and address potential hazards and vulnerabilities within AI systems. Their research is key in finding solutions to prevent unwanted behavior from AI systems and ensure that they act in an aligned way.
How Successif can help
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