Introspection Probe Research Engineer, Development and Infrastructure, Gemini Security, DeepMind

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.

As a Research Engineer on the Gemini Security team, you will help build detection methods and interventions for protecting Gemini from unauthorized distillation.

Artificial intelligence will be one of humanity’s most transformative inventions. At 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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Research, build and land improvements (training and inference) for Gemini security introspection heads.
• Research, build and land real-time interventions triggered by introspection heads.
• Partner with introspection team to improve heads training, serving and deployments.

Minimum qualifications:

• Bachelor's degree in Arts or Science in Computer Science, or a related technical field, or equivalent practical experience.
• Experience with large-scale LLM training and serving infrastructure.
  
• Experience training security or safety classifiers for large AI models.
• Experience deploying security or safety classifiers.

Preferred qualifications:

• 2 years of experience in software development or engineering.
• Experience building real-time interventions for security, safety or anti-abuse in large-scale AI systems.
• Exceptional communication skills with the ability to influence cross-functional stakeholders and executives.
• A deep passion for AI technology and all of its possibilities.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA; San Francisco, CA, USA.

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.