Senior Security Data Engineer at Censys in Remote

Company Background Censys’ mission is to be the one place to understand everything on the internet. Frustrated by the lack of trustworthy Internet intelligence, we set out to create the industry’s most comprehensive, accurate, and up-to-date map of the Internet. Today, Censys delivers real-time Internet intelligence and actionable threat insights to global governments, over 50% of the Fortune 500, and leading threat intelligence providers worldwide. Location: This position is remote within the United States. Role Summary: We’re looking to hire a Senior Security Data Engineer to analyze large-scale Internet data and help build the features, labels, and datasets that power our security-focused Artificial Intelligence (AI) / Machine Learning (ML) models. In this role, you will help turn raw Internet telemetry into enriched, model-ready data that improves how we classify and understand hosts, services, infrastructure, and more across the Internet. Your core focus areas will support such systems so they have the labelled security data required to classify entities as benign, suspicious, or malicious. This will add further AI powered solutions to support our Security Operations Center (SOC) initiatives. At Censys, we believe in working iteratively, but we’re always thinking about the big picture. We’re expanding our data platform and model-driven capabilities to make the Internet more explainable by adding richer context, improving classification, and showing complex relationships across assets and services. We’re looking for someone with an ownership mindset, is curious, can provide mentorship, and has a collaborative spirit for our mission. This role is intentionally distinct from a SOC analyst, threat hunter and rapid response type work; instead, it focuses on the context side of the problem: transforming labels, expert input, and telemetry into scalable model inputs and security-relevant data products. What You’ll Do: 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 Skills You Have: 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 Things that make you stand out: Experience building feature pipelines, labeling systems, or training datasets for security, fraud, reputation, or risk scoring models Experience with Internet measurement, asset intelligence, network security, or large-scale telemetry analysis Familiarity with common Internet protocols and technologies such as HTTP, TLS, DNS, SSH, SMTP, and PKI/certificates Familiarity with ML techniques such as classification, clustering, similarity scoring, anomaly detection, or data science in general Understanding of how attackers, exposed services, misconfigurations, and infrastructure patterns can manifest in Internet-scale data For high cost of living areas (San Francisco Bay, New York City, and Seattle), the expected salary range for this position is $180,000 USD - $212,000 USD, plus bonus eligibility and equity. For other US locations, the expected salary range for this position is $153,000 USD - $180,000 USD, plus bonus eligibility and equity. Actual salary depends on level of experience and geographic location. In addition to our great compensation package, our benefits are effective on day one and include but are not limited to: 401k match, health, vision, dental, and more! Please see our careers page for more details. Our roots are in Ann Arbor, Michigan and our innovation is fueled by the team’s global perspectives. For this role, we are open to remote employees across the continental US. California Privacy Rights Notice Pursuant to the California Consumer Privacy Act (CCPA), we are providing you with notice that we collect personal information from job applicants for business purposes, including evaluating your candidacy for employment, conducting interviews, and, if applicable, completing the hiring process. The categories of information we may collect include identifiers (such as name and contact information), professional or employment-related information (such as work history, education, and references), and other information you provide in your application. We do not sell or share your personal information. For more information on how we use and protect your personal information, and your rights under the CCPA, please refer to our Privacy Policy.