Research Engineer, AGI Safety and Alignment, DeepMind

Research new alignment methods, studying alignment failures, and applying AGI-scalable alignment techniques to frontier models.Develop adversarially robust AGI control systems and implement them in production.Research interpretability techniques to understand what AI systems are thinking.Work with product teams to ensure that our research is correctly adopted.Minimum qualifications:Bachelor's degree in Computer Science, a related Software Engineering field, or equivalent practical experience.3 years of experience in software development, ML engineering, or ML research.Experience working with research teams.Preferred qualifications:Experience conducting or contributing to applied research to improve the safety and alignment of frontier AI systems.Experience with training large models (e.g., supervised fine-tuning, RLHF).At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.The Artificial General Intelligence (AGI) Safety and Alignment Team (ASAT) aims to reduce existential and catastrophic risk from AGI and eventually Artificial Superintelligence (ASI). We research novel techniques and work with the rest of GDM and Google to apply them. ASAT has sub-teams specialising in making future Geminis more thoroughly aligned by finding and fixing sources of misalignment and exploring alignment techniques with better generalization. Preparing for future AGI risks by simulating them today and using interpretability techniques to understand AI and solve practical problems like model forensics or eval awareness. Building control for GDM’s agents as defense-in-depth against potential misaligned internal deployments. Researching training techniques, like debate, for aligning superhuman AI and ways to retain, improve, and measure monitorability. Researching and implementing ways to assess the ways in which a given model might be imperfectly aligned and developing and implementing tools and AI assistance that accelerates safety research.Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $174000 - $252000 (USD) + 15% bonus target + equity + benefitsLearn more about benefits at Google.Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.Note: By applying to this position you will have an opportunity to share your preferred working location from the following: San Francisco, CA, USA; Mountain View, CA, USA; New York, NY, USA.Bachelor's degree in Computer Science, a related Software Engineering field, or equivalent practical experience.3 years of experience in software development, ML engineering, or ML research.Experience working with research teams.