Job description

WHO WE ARE We’re 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 ic3.gov. 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 reddit.com. You can see a demo here loom.com. This is a rare chance to join early and help scale to $30M+ in revenue in the next 12 months. WHAT YOU’LL DO Ownership is everything here. 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. Petra is a premium product and it's everyone's job to make sure it stays that way. That means 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. Concretely, you will: - 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. Our stack is Python, Node, TypeScript, and React... for now. WHO YOU ARE - 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. Bonus if you've worked in high-stakes domains like quantitative finance or fraud detection. - 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. THE TEAM We're small and high-caliber. Our founders are ex-Abnormal Security, Palo Alto Networks, and Bridgewater. Other early team members include: - A Sequoia-backed founder - An engineering leader from Anduril - Quant researchers and engineers from IMC, SIG, Citadel, and Cubist You'll work directly with people who are exceptional at what they do. BENEFITS AND PAY: - Competitive salary. We pay top dollar for exceptional researchers. - Equity - Healthcare, dental, vision - Lunch and dinner when working in the office - 401K - Commuting stipend - Equinox discount - Relocation support This role is in-person, here in SF. ---- Petra is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by applicable law. We are committed to building a diverse and inclusive team and welcome applicants of all backgrounds.

Requirements

Must-haves

Ownership is everything here. 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.
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.
Our stack is Python, Node, TypeScript, and React... for now.
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.
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.
We're small and high-caliber. Our founders are ex-Abnormal Security, Palo Alto Networks, and Bridgewater. Other early team members include:
A Sequoia-backed founder
An engineering leader from Anduril
Quant researchers and engineers from IMC, SIG, Citadel, and Cubist
You'll work directly with people who are exceptional at what they do.
Competitive salary. We pay top dollar for exceptional researchers.
Healthcare, dental, vision
Lunch and dinner when working in the office
Commuting stipend
Equinox discount
Relocation support

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillmmlmachine learningpythontypescriptreact

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k