Staff/Senior Quantitative Researcher

Petra Security•San Francisco, CA

1d•Onsite

About The Position

We are on a mission to stop the most dominant cyberattacks on the planet. Cybersecurity titans are born when a new attack vector overwhelms existing defenses. When ransomware ran rampant, CrowdStrike emerged as the category leader for securing user endpoints. Today, AI has made account compromise the #1 cybercrime. LLM-powered phishing messages get past email security, allowing attackers to compromise accounts and exfiltrate sensitive data in minutes. Incumbents can't keep up. They catch these attacks late, or miss them altogether. Enter Petra, security for when no perimeter remains. We are building an AI-driven Detection and Response platform to catch and remove attackers before they can act. We've grown very quickly, reaching mid-7-figures in ARR in under a year and then doubling ARR in the past few months— we now protect over 2.5 million users across 10,000+ businesses. We price premium, yet have extremely low customer churn. Our customers consistently tell us that Petra is the best product they've ever used. This is a rare chance to join early and help scale to $30M+ in revenue in the next 12 months.

Requirements

5+ years of quantitative/machine learning research experience, with meaningful time designing, training, evaluating, and shipping models in production systems at scale.
Strong quantitative fundamentals: probability & statistics, linear algebra, linear and non-linear modeling, NLP.
Experience training & deploying models in production: You know how to pick the right model for the job. Just as importantly, you know the limitations of each modeling approach you consider.
Strong engineering fundamentals — you write clean, production-grade code and are comfortable owning a system end to end, not just the modeling layer.
Experience working with real-time or streaming data pipelines, feature stores, high-performance databases, and distributed systems.
High agency and high output.
Sharp and scrappy.
Comfortable in a small-team, high-autonomy environment.
Proud of your craft.