Senior Security Data Engineer

Job Description: Analyze Censys telemetry and derived datasets to identify signals that improve AI/ML model training for classification that affects security outcomes Build and improve training and evaluation datasets using Internet telemetry, manually curated labels, and analyst-reviewed data Drive feature discovery, feature selection, and labelling strategies for models that classify entities as benign, suspicious, or malicious Work on multi-layer labeling and classification problems, where categories such as device type, router, honeypot, or edge service may need to be identified before risk classification Partner with Research / Detection teams to translate security domain expertise into actionable workflows Collaborate with ML engineers and software engineers to ensure features, labels, and model inputs are practical to productionize Contribute to feedback loops and evaluation frameworks that improve precision, recall, confidence, and coverage over time Build tooling to support the efforts listed above Requirements: 5+ years of experience in research or software engineering with a security data focus Experience analyzing large datasets and turning ambiguous data into usable information that solves security problems Strong programming skills in Go/Python (or similar), plus experience using SQL (or similar) tools to analyze large datasets Strong communication skills and the ability to work effectively with researchers, ML engineers, software engineers, and other security experts Comfort working with security-relevant data and applying technical judgment to questions about Internet-exposed hosts, services, and infrastructure. Benefits: 401k match health vision dental more!