Application Guide
How to Apply for Machine Learning Researcher
at Gray Swan
🏢 About Gray Swan
Gray Swan is an AI security company at the forefront of ensuring safe AI deployment, specializing in automated risk assessment tools. Working here means contributing to critical safety evaluations of the most advanced AI models, directly impacting responsible AI innovation.
About This Role
As a Machine Learning Researcher, you will conduct AI safety research to identify and defend against failure modes in cutting-edge systems. Your work involves stress-testing models to discover emerging vulnerabilities and developing research-backed solutions, informing official safety evaluations for enterprises and policymakers.
💡 A Day in the Life
Your day might start with a stand-up discussing ongoing red-teaming experiments, followed by coding a new automated evaluation pipeline. Afternoons could involve analyzing model outputs for novel failure modes, reviewing recent safety literature, and collaborating with engineers to integrate findings into Gray Swan's tools.
🚀 Application Tools
🎯 Who Gray Swan Is Looking For
- Has a strong publication record in AI safety, robustness, or alignment research (e.g., adversarial robustness, red-teaming).
- Hands-on experience stress-testing large language models or other generative AI systems, with a portfolio of discovered failure modes.
- Proficient in Python and deep learning frameworks (PyTorch, JAX), with ability to design and run automated evaluation pipelines.
- Thinks critically about AI risk scenarios and can translate research findings into actionable recommendations for deployment.
📝 Tips for Applying to Gray Swan
Highlight specific AI safety projects or papers, especially those involving red-teaming or vulnerability discovery.
Showcase your ability to automate evaluations—mention any frameworks you built for stress-testing models.
Tailor your resume to emphasize experience with cutting-edge models (GPT-4, Claude, Gemini) and their failure modes.
Include a brief statement on why AI safety is personally important to you and how your values align with Gray Swan's mission.
If you have open-source contributions (e.g., to safety toolkits like ART, Foolbox, or custom red-teaming tools), link them prominently.
✉️ What to Emphasize in Your Cover Letter
['Your commitment to AI safety and understanding of high-risk failure modes (e.g., jailbreaks, hallucinations, bias).', 'Concrete examples of stress-testing AI models and the novel vulnerabilities you uncovered.', "How your research can directly improve Gray Swan's automated risk assessment tools.", 'Your ability to communicate technical findings to both technical and non-technical stakeholders.']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Read Gray Swan's blog posts and papers on AI safety evaluation methodologies.
- → Understand their product offerings—how they automate risk assessment for enterprises.
- → Study recent AI safety incidents (e.g., jailbreaks of GPT-4, Gemini bias issues) and how Gray Swan might address them.
- → Familiarize yourself with the company's leadership and their background in AI security.
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Submitting a generic application without mentioning AI safety or Gray Swan's specific mission.
- Overemphasizing pure ML performance metrics (e.g., accuracy) without discussing safety implications.
- Failing to provide concrete examples of stress-testing or vulnerability discovery in your experience.
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!