Research Scientist, AI Secure Code, DeepMind

• Contribute to GDM's Cyber Strike initiative, collaborating across organizations (DeepMind, Cloud Security, etc.) to build high-quality cybersecurity datasets, benchmarks, and evaluation platforms for vulnerability finding and fixing.
• Design, implement, and maintain scalable software infrastructure for CodeMender’s vulnerability detection and remediation services.
• Build evaluation pipelines, benchmarks, and leaderboards to rigorously measure agent performance.
• Optimize system performance, latency, and resource utilization for serving large models.
• Collaborate with product and platform teams to gather requirements and deploy research-based solutions into Google's developer tools and workflows.

Minimum qualifications:

• PhD degree in Computer Science or Computer Engineering, similar technical field of study (e.g., Electrical Engineering, Mathematics, Information Technology) or equivalent practical experience.
• Experience with vulnerability research (e.g., auditing, reverse engineering, exploitation).
• Experience building infrastructure, developer tools, or ML-based applications.
• Publication record in AI conferences (e.g., NeurIPS, CVPR, ICCV, ICLR).

Preferred qualifications:

• Bachelor's or Master's in Computer Science or equivalent experience.
• Experience building AI tools/agents for coding.
• Strong proficiency in Python, C++, or Go.
• Familiarity with machine learning frameworks and techniques (fine-tuning, reinforcement learning).
  
• Ability to self-initiate and a passion for the mission of AI safety and security.

• PhD degree in Computer Science or Computer Engineering, similar technical field of study (e.g., Electrical Engineering, Mathematics, Information Technology) or equivalent practical experience.
• Experience with vulnerability research (e.g., auditing, reverse engineering, exploitation).
• Experience building infrastructure, developer tools, or ML-based applications.
• Publication record in AI conferences (e.g., NeurIPS, CVPR, ICCV, ICLR).