Research Engineer, Frontier Safety Risk Assessment, DeepMind

Research Engineer, Frontier Safety Risk Assessment, Deep Mind

Deep Mind – San Francisco, CA, USA;
London, UK;
New York, NY, USA – can choose your preferred location.

• Bachelor's degree or equivalent practical experience.
• 5 years of experience in deep learning or with large foundation models.
• Experience designing and implementing AI experiments and systems using Python.
• Experience identifying, assessing, or mitigating advanced AI model risks in production systems.
• Experience communicating technical concepts or research insights to technical stakeholders.

• Ph.D. in Computer Science, Machine Learning, or related technical field.
• Experience in frontier risk assessment, AI safety, and alignment.
• Experience collaborating on or leading applied research projects.
• Engineering experience with Large Language Model (LLM) training and inference.
• Track record of publications at venues such as NeurIPS, ICLR, ICML, RL/DL workshops, EMNLP, AAAI, or UAI.

• Drive research to measure, assess and prioritize risks from frontier AI models.
• Identify and analyze emerging risk pathways in areas including loss of control, ML R&D, cybersecurity, and harmful manipulation.
• Design and develop new methods for measuring pre‑mitigation and post‑mitigation risk, incorporating forecasting and scenario planning.
• Implement research findings and build technical solutions using Python, interacting with various codebases.
• Prioritize research and engineering efforts within pragmatic constraints of compute and time to maximize value of information.

US: $174,000 – $253,000 (USD) + 15% bonus target + equity + benefits.

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English proficiency is a requirement for all roles unless otherwise stated in the job posting.