Quantitative Researcher

Petra Security•San Francisco, CA

2d•Onsite

About The Position

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. This is a rare chance to join early and help scale to $30M+ in revenue in the next 12 months. You'll be responsible for our core ML detection research, and the models you design and deploy are what separate Petra from every other player in this space. You won't just train models — you'll talk to customers, understand the attacks they're facing, and think creatively about how to find the next signal that widens the gap between us and second place.

Requirements

1-4 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 contributing to systems 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. You identify the problem, propose the solution, and execute. You're constantly looking for ways to expand your scope and circle of competence.
Sharp and scrappy. You learn fast: you ask the right questions and figure it out. You ship fast: you find the 90/10 and don't let perfect be the enemy of done.
Comfortable in a small-team, high-autonomy environment. The scope of your work is rarely handed to you, and you wouldn't have it any other way.
Proud of your craft. You care about building things that work well and hold up over time.

Nice To Haves

Bonus if you've worked in high-stakes domains like quantitative finance or fraud detection.

Responsibilities

Build and evolve our detection models. Working closely with our CTO and Head of Machine Learning, you'll help design and build the ML models that identify account compromise in real time.
Take models from research to production. You don't just care about model performance in a notebook. You're energized by measuring how your models behave at scale in a live system with real attackers.
Architect for scale. We're growing fast. Nothing excites you more than architecting and implementing an elegant solution that'll handle 10-100x the scale in 6 months.
Develop and push the technical bar. As a core voice on a lean team, your appetite and ability to learn quickly will be crucial to the teams experimentation and collective knowledge. You'll establish patterns, push for correctness, and raise the quality of everything around you.