Remote Staff ML Engineer for Cybersecurity AI

Dragos; United States; Remote; USD 191,000 - 259,000; Full time

Benefits offered by this job

Competitive Equity Package

Comprehensive Benefits Plan

Job summary

Dragos seeks a Staff Machine Learning Engineer to drive production ML design and implementation within the Dragos platform, collaborating across Data Engineers and product teams to deliver AI capabilities that enhance threat detection for ICS/xOT cybersecurity.

You will build scalable models for ICS/xOT security, develop robust data pipelines, and contribute to ML infrastructure with CI/CD and containerized deployments (Kubernetes, Docker).

Qualifications

• 6+ years of engineering experience with at least 4 years focused on machine learning implementations in production environments.
• Strong software engineering foundation with expertise in Python and SQL as well as experience with Go, Rust, Java, or JVM-family languages.
• Experience with ML frameworks such as scikit-learn, PyTorch, TensorFlow, or HuggingFace.
• Experience with LLMs, retrieval-augmented generation (RAG), or advanced NLP techniques is beneficial.
• Proven track record implementing ML solutions delivering measurable business impact.
• Experience with MLOps, including model versioning, monitoring, pipeline orchestration, and deployment in high-reliability environments.
• Familiarity with data pipelines, stream processing, and working with medium-to-large scale datasets.
• Knowledge of containerized deployment solutions and cloud-native architectures.
• Strong communication skills to explain technical concepts to diverse stakeholders and collaborate effectively across teams.
• Cybersecurity domain knowledge, particularly in threat detection, threat intelligence, or IDS/OT operations.

Responsibilities

• Design and implement production-grade machine learning systems for Dragos product capabilities with consideration for cloud and on-premises environments.
• Build and optimize ML model architectures for ICS/OT cybersecurity use cases, including threat detection, asset classification, behavioral analysis, and NLP systems.
• Develop robust data pipelines and ML workflows that integrate with existing data infrastructure for real-time and batch processing.
• Collaborate with OT detection experts to translate research concepts into scalable, production-ready ML systems.
• Partner with Data Engineers to establish data contracts and observability frameworks for ML pipelines, including monitoring, versioning, and deployment best practices.
• Contribute to ML infrastructure improvements, including automated testing frameworks, CI/CD pipelines, and deployment strategies for containerized environments (Kubernetes, Docker).
• Evaluate and adapt state-of-the-art ML research and open-source models to domain-specific cybersecurity applications.
• Troubleshoot and optimize ML model performance in production environments, addressing latency, accuracy, and resource utilization.

Skills

Python

SQL

Go

Rust

Java

scikit-learn

PyTorch

TensorFlow

HuggingFace

LLMs

MLOps

Tools

Kubernetes

Docker

CI/CD

Job description

Dragos seeks a Staff Machine Learning Engineer to drive production ML design and implementation within the Dragos platform, collaborating across Data Engineers and product teams to deliver AI capabilities that enhance threat detection for ICS/xOT cybersecurity.

You will build scalable models for ICS/xOT security, develop robust data pipelines, and contribute to ML infrastructure with CI/CD and containerized deployments (Kubernetes, Docker).