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The Role
The Machine Learning Engineer will propose technical initiatives, lead design discussions, translate challenges into plans, and uphold engineering standards.
Summary Generated by Built In
About RunSybil
RunSybil is an AI security startup scaling offensive security services by automating hacker intuition. We’re building Sybil: an AI-powered penetration testing product that finds vulnerabilities faster than human hackers. Backed by strong investor support and early customer traction, our team is composed of experts from the likes of OpenAI, Meta, Mandiant, Palantir, Cruise, and Trail of Bits.
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 Has A Mix of The Following:
- 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.
What We Offer:
- Competitive Salary: Attractive startup compensation package with equity options
- Benefits: Excellent medical, dental, and vision plans. Unlimited PTO
- Growth Opportunities and Early Impact: Work directly with and learn from industry leaders while driving significant impact in our fast-growing security startup
We understand not every applicant will meet every qualification. We value hard work and potential, and still want to hear from you!
Skills Required
- 4+ years of experience designing experiments and managing data infrastructure
- Experience working with security data problems
- Understanding of both modern and classic machine learning techniques
- Comfortable with Jupyter notebooks and building data pipelines
RunSybil Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RunSybil and has not been reviewed or approved by RunSybil.
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Healthcare Strength — Healthcare coverage is described as 100% employer-paid for employees and 80–85% for dependents, with travel insurance, pet-insurance discounts, and access to mental-health, primary-care, coaching, fitness, and navigation partners plus an EAP. These elements point to broad coverage and strong day-to-day support for a startup.
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Leave & Time Off Breadth — Time off is presented as unlimited PTO with a suggested minimum of 20 days and 14 company holidays. This added clarity around a floor can make the policy more usable in practice.
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Parental & Family Support — Parental leave is listed at 12 weeks paid with a flexible return-to-work policy. Company materials frame this as more explicit than many early-stage peers.
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The Company
What We Do
RunSybil's mission is to automate hacker intuition. We offer active defense capabilities based on the state-of-the-art in AI and exploitation. We're taking Dixie Flatline out of Neuromancer and putting him on every security team. Stay tuned ?
