Trail of Bits is launching a Machine Learning Security Research Fellowship to address the security risks associated with cutting-edge AI/ML systems and to provide researchers with high-impact industry experience at the intersection of AI/ML research and real-world security.
Requirements
- Strong hands-on experience with modern AI/ML frameworks (PyTorch, JAX, TensorFlow), foundation models, and the full AI/ML research workflow including experimentation, training, and evaluation.
- Demonstrated ability to think adversarially about systems, identify edge cases, or explore failure modes—even without formal security training. Interest in adversarial AI/ML, robustness, or AI safety highly valued.
- Proficient in Python and comfortable with systems programming. Experience implementing research prototypes and experimental frameworks.
- Track record of high-quality research through publications, preprints, workshop papers, or significant open-source contributions that demonstrate deep AI/ML expertise.
- Self-directed researcher capable of defining research questions, designing experiments, and driving projects to completion with minimal supervision.
Responsibilities
- Conduct original security research on frontier AI/ML systems while collaborating with our AI Assurance team on high-stakes client engagements.
- Gain hands-on experience evaluating the security of state-of-the-art AI/ML systems deployed by top AI organizations, working on problems that represent the cutting edge of AI/ML security.
- Design and implement new attack methodologies, defensive techniques, and evaluation frameworks for adversarial AI/ML scenarios including model poisoning, adversarial examples, jailbreaks, and data extraction.
- Build and release AI/ML security tools and frameworks that benefit the broader research community, with support for open-source contribution as a core fellowship objective.
- Work alongside Trail of Bits' security research team, gaining exposure to security engineering practices while maintaining focus on research excellence.
- Produce publishable research, technical blog posts, and open-source tools that advance the state of AI/ML security understanding—with explicit support for academic publication.
- Pursue your own AI/ML security research interests with support from Trail of Bits' research team, with opportunities to publish findings and present at leading conferences.
Other
- Currently pursuing or recently completed (within 2 years) a PhD in machine learning, computer science, statistics, or related field, with strong research credentials.
- Can explain complex technical concepts clearly to diverse audiences and synthesize research findings into actionable insights.
- One-year commitment with potential pathway to full-time position.
- Travel funding for conference presentations and research community engagement.
- Regular collaboration with Trail of Bits researchers and exposure to client work.
