Cybersecurity Research Engineer, Gemini AI

Google Inc.; San Francisco (CA); On-site; USD 174,000 - 252,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

Google DeepMind is seeking a Research Engineer, Cyber Gemini, to advance Gemini and CodeMender through autonomous vulnerability discovery and fixing at the intersection of research and engineering. You will design experiments, run large-scale tests, and build scalable infrastructure while collaborating with teams across the organization.

The role emphasizes applying ML to cybersecurity challenges, with responsibilities spanning dataset creation, model evaluation, and system optimization for

Qualifications

• Bachelor's degree in Computer Science or related field, or equivalent practical experience.
• 5 years of experience with large language models, including pre-training or fine-tuning.
• Experience with cybersecurity research preferred.

Responsibilities

• Contribute to Gemini Cyber, collaborating across organizations to build high-quality training recipes, cybersecurity datasets, benchmarks, and evaluation platforms for vulnerability finding and fixing.
• Build datasets (RL environments, SFT data) and iterate on post-training recipes.
• Integrate novel ML and agentic techniques into research prototypes.
• Build evaluation pipelines, benchmarks, and leaderboards to rigorously measure agent performance.
• Optimize system performance, latency, and resource utilization for serving large models.

Skills

LLM experience

Education

Bachelor's degree in Computer Science

Job description

Google DeepMind is seeking a Research Engineer, Cyber Gemini, to advance Gemini and CodeMender through autonomous vulnerability discovery and fixing at the intersection of research and engineering. You will design experiments, run large-scale tests, and build scalable infrastructure while collaborating with teams across the organization.

The role emphasizes applying ML to cybersecurity challenges, with responsibilities spanning dataset creation, model evaluation, and system optimization for