Applied ML Researcher — Real-Time Cyber Defense

Petra Security; San Francisco (CA); On-site; USD 210,000 - 320,000; Full time

Benefits offered by this job

Equity

Healthcare

Dental

Vision

Lunch and dinner when in office

401K

Commuting stipend

Relocation support

Equinox discount

Job summary

Petra Security in San Francisco invites a machine learning researcher to own core detection research and develop real-time account-compromise models. You will work closely with our CTO and Head of ML to translate ideas into production systems and scale arquitectures for rapid growth.

You will drive model quality, participate in customer-facing discussions, and help push the technical boundaries of our AI-driven detection platform.

Qualifications

• 1–4 years of ML research experience with production models.
• Strong quantitative fundamentals: probability, statistics, linear algebra, NLP.
• Experience training and deploying models in production environments.
• Strong engineering fundamentals and production-grade code.
• Experience with real-time or streaming data pipelines and distributed systems.
• High agency, fast learner, and autonomous work style.

Responsibilities

• Build and evolve Petra's detection models in collaboration with the ML leadership.
• Take models from research to production and measure live-system performance.
• Architect scalable solutions capable of 10–100x growth within 6 months.
• Develop and raise the technical bar, establishing patterns and quality.

Skills

ML research 1-4y

Quant fundamentals

Production ML

Engineering fundamentals

Real-time data pipelines

Fast, autonomous worker

Tools

TensorFlow/PyTorch

Data pipelines

Distributed systems

Feature stores

SQL/NoSQL databases

Job description

Petra Security in San Francisco invites a machine learning researcher to own core detection research and develop real-time account-compromise models. You will work closely with our CTO and Head of ML to translate ideas into production systems and scale arquitectures for rapid growth.

You will drive model quality, participate in customer-facing discussions, and help push the technical boundaries of our AI-driven detection platform.