Senior Machine Learning Engineer
Build and deploy AI-driven cybersecurity models to detect real-time account compromise and stop attackers before they act, using Python and distributed systems.
- Compensation
- Not disclosed
- Location
- San Francisco
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 4+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- 4+ years of machine learning engineering experience, with meaningful time shipping models in production systems at scale.
- Strong quantitative fundamentals: probability & statistics, linear algebra, anomaly detection, behavioral 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. Bonus if you've worked in high-stakes domains like quantitative fina
- 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.
Full description
Who We AreWe’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. 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 — 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. You can see a demo here.
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 platform, and the systems you build 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 design and build the ML systems 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.
- Raise the technical bar. As a senior voice on a lean team, your instincts and opinions shape how we build. You'll establish patterns, push for correctness, and raise the quality of everything around you.
Our stack is Node, TypeScript, React, and Python... for now.
Who You Are
- 4+ years of machine learning engineering experience, with meaningful time shipping models in production systems at scale.