Senior AI/ML Engineer

🔥 13 hours ago

🇺🇸 United States – Remote

💵 $190k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Dragos, Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2016

🏭 Manufacturing

📦 Logistics

💼 Consulting

💰 $74M Series D - Dragos on 2023-09

Manufacturing • Logistics • Consulting

Dragos, Inc. is a cybersecurity company specializing in operational technology (OT) and industrial control systems (ICS) protection for critical infrastructure. It provides an OT-native platform that delivers asset visibility, vulnerability management, threat detection, and response playbooks, backed by threat intelligence, managed services (including OT Watch and incident response), training, and compliance support. Dragos focuses on defending sectors like energy, utilities, manufacturing, transportation, and other industrial environments through a combination of software, intelligence, and expert services.

📋 Description

• Apply clustering, classification, anomaly detection, and other established ML techniques to cybersecurity data problems in the ICS/OT domain. • Integrate ML model outputs into existing data pipelines and product workflows for batch and near-real-time processing. • Translate research outputs into reliable pipeline components and understand model behavior. • Partner with Data Engineers on data contracts, observability, and failure modes. • Evaluate open-source and third-party models for specific use cases. • Write maintainable Python or Rust code. • Troubleshoot production ML components, including output quality, data drift, and edge cases. • Explain model behavior, uncertainty, and appropriate downstream use. • Collaborate with AI Engineers, Data Engineers, and product teams to bring ML capabilities into the Dragos platform.

🎯 Requirements

• 5+ years of software engineering experience, with meaningful time spent working with ML outputs or data pipelines in a production context. • Strong Python skills; SQL proficiency; comfort reading and reasoning about data at scale. • Hands-on experience applying ML techniques, including clustering (k-means, DBSCAN, hierarchical), classification, and anomaly detection. • Familiarity with scikit-learn and the surrounding Python ML ecosystem; responsible use of neural networks. • Solid understanding of data pipeline concepts, transformations, failure modes, and observability. • Ability to evaluate whether model outputs are trustworthy for a given use case. • Strong written and verbal communication; able to explain tradeoffs to technical and non-technical stakeholders. • All new hires must pass a background check as a condition of employment. • Experience with graph-based representations of network topology or asset relationships is nice to have. • Familiarity with stream processing or event-driven architectures is nice to have. • Exposure to Docker and Kubernetes as a consumer/deployer is nice to have.

🏖️ Benefits

• Competitive Equity Package • Comprehensive Benefits Plan

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