Machine Learning Engineer

Department: Engineering

Location: San Francisco / New York CIty

Employment Type: FullTime

About RunSybil

Founded in 2023 by Ari Herbert-Voss and Vlad Ionescu, RunSybil is on a mission to automate hacker intuition. We’re building Sybil: an AI-driven pentester that discovers vulnerabilities before they’re exploited. As adversaries adopt AI to increase their attack surface, we’re putting cutting-edge offensive security into the hands of defenders. Backed by strong investor support and early customer traction, our team is composed of experts from OpenAI, Meta, Mandiant, Palantir, Cruise, Trail of Bits, and Aptiv.

About this Role

We are seeking talented engineers intent on changing the security industry. If you have experience on fast-moving teams and pushing out high quality experiments: we want to talk to you.

What You'll Do:

• Propose and implement technical initiatives based on product roadmap needs

• Lead technical design discussions, contribute to team decisions, and provide feedback on engineering approaches

• Translate ambiguous technical challenges into actionable plans, and execute them in collaboration with the team

• Serve as the cornerstone of our engineering culture by setting and upholding exemplary standards for code quality, practices, and craftsmanship

We’re looking for someone who brings:

• Experience working with security data problems

• MS or PhD in a quantitative discipline is nice but certainly not required - strong bias for building product-informing experiments versus published works

• 4+ years of experience designing experiments and managing data infrastructure

• Understanding of both modern and classic machine learning techniques

• Equally comfortable with Jupyter notebooks and building data pipelines

• Seeks autonomy, creative problem-solving, and moving quickly in an ambiguous environment

Location: Hybrid role based in New York City. Some travel may be required.

Diverse teams build better products. RunSybil is committed to hiring people who bring different perspectives, lived experiences, and backgrounds to our work. We encourage candidates of all races, ethnicities, gender identity and expression, sexual orientation, disability or medical conditions, ages, religions, and socioeconomic backgrounds to apply. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. If you're excited about this role but don't check every box, we still want to hear from you.