Research Engineer, Model Security Against Adversarial Misuse

• Develop and deploy advanced AI/ML solutions to identify and mitigate potential cybersecurity misuse, leveraging prompt engineering, machine learning, and post-training.

• Implement advanced post-training algorithms to optimize Gemini for cybersecurity misuse prevention.

• Diagnose and interpret training outcomes (regressions, gains), and propose and implement solutions to improve model capabilities.

• Actively monitor and evolve the overall defense system's mitigation capability through system metric design and improvement.

• Develop reliable automated evaluation pipeline for cybersecurity misuse mitigation metrics that are strongly correlated with human expert  judgment of threat severity.

• Construct adversarial evaluation benchmarks to probe the limits and failure modes of cybersecurity misuse mitigation performance.
  
  

• BSc, MSc or PhD/DPhil degree in computer science, applied stats, machine learning or similar experience working in industry

• Experiences in fine-tuning and adaptation of LLMs (e.g. advanced prompting,  supervised fine-tuning, RLHF)

• Cybersecurity knowledge and background is a great advantage.

• Deep understanding of machine learning and statistics 

• Strong knowledge of systems design and data structures

• Proven experience with TensorFlow, JAX, PyTorch, or similar leading deep learning frameworks

• Recent experience conducting applied research to improve the quality and training/serving efficiency of large transformer-based models

• A passion for Artificial Intelligence and Cybersecurity.

• Excellent communication skills and proven interpersonal skills, with a track record of effective collaboration with cross-functional teams

The US base salary range for this full-time position is between $166,000 - $291,000 + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.