Application Guide
How to Apply for Forward Deployed Engineer – Machine Learning
at Gray Swan
🏢 About Gray Swan
Gray Swan is an AI security company focused on proactively assessing AI model risks, operating at the intersection of cutting-edge AI development and enterprise security. Unlike traditional security companies, they work on the frontier of AI safety, identifying vulnerabilities before they become widespread threats. This makes them uniquely positioned for engineers who want to tackle novel problems in AI safety rather than just implementing established solutions.
About This Role
As a Forward Deployed Engineer – Machine Learning at Gray Swan, you'll be stress-testing agentic AI systems in controlled environments while helping enterprise clients deploy AI safely at scale. This role involves translating theoretical AI safety research into practical tools and playbooks that prevent real-world AI failures. You'll work on the 'messy edge' of AI deployment where novel safety challenges emerge, making this role critical for shaping how organizations adopt advanced AI responsibly.
💡 A Day in the Life
A typical day might involve designing and running experiments to stress-test agentic AI systems in controlled lab environments, analyzing results to identify novel safety vulnerabilities. You'd collaborate with both research and product teams to translate findings into practical safety tools or deployment playbooks, while also potentially consulting with enterprise clients on their specific AI deployment challenges. The role balances hands-on technical work with strategic thinking about how to anticipate and prevent AI risks before they impact real systems.
🚀 Application Tools
🎯 Who Gray Swan Is Looking For
- Has hands-on experience deploying machine learning models in production environments, specifically with enterprise-scale systems where reliability and safety are paramount
- Demonstrates a research-oriented approach to AI safety problems, able to systematically investigate vulnerabilities in AI systems rather than just applying existing solutions
- Possesses experience with both the technical implementation of AI systems and the strategic considerations of AI safety in organizational contexts
- Thrives in ambiguous, frontier environments where problems aren't well-defined and requires creating novel solutions rather than following established patterns
📝 Tips for Applying to Gray Swan
Highlight specific examples where you've identified and addressed AI safety or reliability issues in production deployments, not just model development
Demonstrate your ability to think 'three steps ahead' about AI risks by discussing how you've anticipated problems before they occurred in previous roles
Show familiarity with agentic AI systems specifically, as this is mentioned in the job description as a core testing area
Emphasize any experience working at the intersection of research and practical implementation, as Gray Swan values turning insights into real-world solutions
Tailor your resume to show progression from identifying AI problems to implementing safety solutions, mirroring their 'uncover problems → create solutions' workflow
✉️ What to Emphasize in Your Cover Letter
["Your experience with enterprise AI deployment challenges and how you've addressed safety concerns in production environments", 'Specific examples of identifying novel AI risks or vulnerabilities before they became widespread issues', 'How you balance research-oriented investigation with practical implementation to create usable safety solutions', "Your approach to working on ambiguous, frontier problems where established solutions don't yet exist"]
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Explore Gray Swan's public materials to understand their specific approach to AI risk assessment versus traditional AI security companies
- → Research current challenges in agentic AI safety specifically, as this is mentioned as a core testing area in the role
- → Look into the types of enterprise clients they likely serve and the specific deployment challenges those organizations face
- → Understand the broader AI safety landscape to position Gray Swan's approach relative to other organizations in the space
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Focusing only on model development metrics (accuracy, F1 scores) without discussing deployment safety and reliability considerations
- Presenting yourself as purely a researcher without demonstrating ability to implement practical, production-ready solutions
- Using generic AI/ML terminology without showing specific understanding of safety challenges in enterprise deployment contexts
📅 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!