Staff ML Application Engineer

📋 Description

• Apply clustering, classification, anomaly detection to cybersecurity data in ICS/OT.
• Integrate ML outputs into data pipelines and product workflows, batch and near-real-time.
• Understand model behavior and translate outputs into reliable pipeline components.
• Collaborate with Data Engineers to ensure ML pipelines have data contracts and observability.
• Evaluate open-source and third-party models for fit to use cases and tradeoffs.
• Write clean, maintainable Python or Rust code for others to review.

🎯 Requirements

• 4+ years of software engineering with ML outputs or data pipelines in production.
• Strong Python skills; SQL proficiency; comfortable reading data at scale.
• Hands-on ML: clustering (k-means, DBSCAN, hierarchical), classification, anomaly detection.
• Familiarity with scikit-learn; know how to use standard ML models responsibly.
• Strong data-pipeline concepts: data flow, transformation, failures, observability.
• Ability to judge if model outputs are trustworthy for a use case.

🎁 Benefits

• Competitive Equity Package
• Comprehensive Benefits Plan
• Remote-friendly culture with global teams