Research Engineer, Frontier Safety Risk Assessment, DeepMind

Research Engineer, Frontier Safety Risk Assessment, DeepMind DeepMind – Locations: San Francisco, CA, USA; London, UK; New York, NY, USA; +2 more cities. Minimum qualifications: 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. Preferred qualifications: Ph.D. in Computer Science, Machine Learning, or a related technical field. Experience in areas such as frontier risk assessment or mitigations, AI safety, and alignment. Experience collaborating on or leading applied research projects. Engineering experience with Large Language Model (LLM) training and inference. A track record of publications at venues such as NeurIPS, ICLR, ICML, RL/DL workshops, EMNLP, AAAI, or UAI. About the job At DeepMind, research-focused Software Engineers are embedded throughout the company, allowing them to set up large-scale tests and deploy promising ideas quickly and broadly. Engineers work on real‑world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, and core search. They stay connected to their research roots by partnering with universities and publishing papers. Artificial intelligence is one of humanity’s most transformative inventions, and at DeepMind we are a pioneering AI lab focused on safety, ethics, and public benefit. US salary: $174,000 - $253,000 (USD) + 15% bonus target + equity + benefits. Responsibilities Drive novel research to measure, assess, and prioritize risks from frontier AI models. Identify and analyze emerging risk pathways in areas including loss of control, machine learning research and development (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. Equal Opportunity and Anti‑Discrimination Statements Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity or expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents‑to‑be, criminal histories consistent with legal requirements, or any other basis protected by law. #J-18808-Ljbffr Google