As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
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 - $253000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Identify potential harms from misaligned agents and develop strategies for detection and prevention.
- Implement technical controls to monitor agent thoughts, behaviour, and respond to mitigate potential harms.
- Integrate various agent behaviour signals from across the organisation to inform response policies.
- Conduct adversarial testing of controls.
- Work with internal product teams to ensure that control systems are adopted over all high-risk AI surfaces.
Qualifications
Minimum qualifications:
- Bachelor's degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience.
- 2 years of experience in engineering and agentic assistance, including software development in Python.
- Experience working in a frontier AI research and development environment.
- Experience working in a professional software engineering or research team environment.
- Experience working with technical stakeholders.
- Experience in frontier model risk.
Preferred qualifications:
- Experience of engineering or product design for AI tools or assistants, especially those focused on ML Research and Development (R&D).
- Experience with cybersecurity detection and response.
- Experience with collaborating or leading an applied ML project.
- Experience with Large Language Model (LLM) training and inference.
- Knowledge of AI control, chain-of-thought and other monitoring, faithfulness and monitorability and related research areas.