Research Engineer, Frontier Safety Risk Assessment, DeepMind
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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 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.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 various 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 - $253000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
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 (ML) 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.
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