[Remote] Staff ML Application Engineer

Note: The job is a remote job and is open to candidates in USA. Dragos, Inc. is on a mission to defend industrial organizations with best-in-class technology and services in ICS/OT Cybersecurity. They are seeking a Staff ML Application Engineer to integrate machine learning techniques into their product and data pipelines, working closely with AI Engineers and Data Engineers to enhance cybersecurity capabilities.ResponsibilitiesApply clustering, classification, anomaly detection, and other established ML techniques to cybersecurity data problems in the ICS/OT domainIntegrate ML model outputs into existing data pipelines and product workflows, supporting both batch and near-real-time processing patternsUnderstand model behavior and translate research outputs into reliable pipeline componentsWork with Data Engineers to ensure ML-driven stages of the pipeline have clear data contracts, appropriate observability, and sane failure modesEvaluate open-source and third-party models for fit against specific use cases, knowing when to apply an existing tool versus when to escalate to a model-building effortWrite clean, maintainable Python or Rust that other engineers can reason about, test, and extendTroubleshoot ML component behavior in production to diagnose issues with output quality, data drift, or unexpected edge casesCommunicate clearly about what a model is doing, where it's uncertain, and how its outputs should (and shouldn't) be used downstreamSkills4+ years of software engineering experience, with meaningful time spent working with ML outputs or data pipelines in a production contextStrong Python skills; SQL proficiency; comfort reading and reasoning about data at scaleHands-on experience applying ML techniques including clustering (k-means, DBSCAN, hierarchical), classification, and anomaly detectionFamiliarity with scikit-learn and the surrounding Python ML ecosystem; you don't need to have implemented a neural net, but you should know how to use one responsiblySolid understanding of data pipeline concepts: how data flows, where it gets transformed, what can go wrong, and how to make failures visibleAbility to evaluate whether a model's outputs are actually trustworthy for a given use case — not just whether accuracy metrics look goodStrong written and verbal communication; comfortable explaining tradeoffs to both technical and non-technical stakeholdersCybersecurity domain knowledge — especially around threat detection, network behavior, or ICS/OT operations is a meaningful plus, but not a prerequisiteExperience working with graph-based representations of network topology or asset relationshipsFamiliarity with stream processing or event-driven architecturesExposure to containerized environments (Docker, Kubernetes) as a consumer/deployer, not necessarily an operatorBenefitsCompetitive Equity PackageComprehensive Benefits PlanCompany OverviewDragos provides the most effective OT cybersecurity technology for industrial and critical infrastructure to deliver on our global mission: to safeguard civilization. It was founded in 2016, and is headquartered in Hanover, Maryland, USA, with a workforce of 501-1000 employees. Its website is https://www.dragos.com.