Sr. Machine Learning Engineer (Cybersecurity)

TL;DR

Sr. Machine Learning Engineer (Cybersecurity): Design, build, and operate distributed ML systems for petabyte-scale streaming data in real-time threat detection with an accent on reliability, scalability, and performance in production. Focus on productionizing models from research, improving evaluation pipelines, and integrating with big data streaming technologies.

Location: Remote (US), ability to travel to Santa Barbara, CA office a few times per year required

Salary: $160,000-$220,000

Company

Leading provider of AI-powered cybersecurity solutions using self-supervised, context-aware AI for threat detection across cloud, hybrid, and on-premises environments, trusted by US Department of Defense and Intelligence Community.

What you will do

• Design and operate production ML systems for large-scale streaming data
• Own system reliability, performance, and observability in production
• Improve speed and reproducibility of model evaluation and iteration
• Collaborate with researchers to productionize models and integrate into distributed systems
• Contribute to evolving ML systems and infrastructure for better scalability and maintainability

Requirements

• Ability to travel to Santa Barbara, CA office a few times per year
• 5+ years Python experience in production environments
• 5+ years applying machine learning with PyTorch, scikit-learn, pandas, etc.
• Experience building and operating distributed systems (Kubernetes, microservices, streaming)
• Experience improving ML experimentation and evaluation systems
• Experience with big data/streaming technologies (Spark, Flink, or similar)
• Strong mathematical foundation (degree in CS, Math, Stats, Physics, or related)

Nice to have

• Experience with JVM languages (Java, Scala, Kotlin)
• Experience with Javascript/Typescript

Culture & Benefits

• Remote-First work culture
• Competitive healthcare (Medical, Dental, Vision, Accident)
• 401(k) with employer match
• Flexible Spending Account (FSA)
• Paid holidays and flexible PTO

Hiring process

• Focus on real-world production ML experience and reasoning about predictive systems
• Remote interviews early (no AI tools); final in-person interview in Santa Barbara (travel paid)