Staff AI/ML Engineer — Production ML for Cybersecurity

Dragos, Inc.; Lennox Park (MD); On-site; USD 191,250 - 258,750; Full time

Benefits offered by this job

Competitive Equity Package

Comprehensive Benefits Plan

Job summary

Dragos seeks a Staff Machine Learning Engineer to design and deploy production ML systems within the Dragos platform, collaborating with Data Engineers and product teams to advance threat detection and security analysis for ICS/OT applications.

You will build ML solutions including classification, time‑series analysis, anomaly detection, and NLP, applying MLOps, CI/CD, and containerized deployments in Kubernetes and Docker. Remote work with global reach is supported.

Qualifications

• 6+ years of engineering experience with at least 4 years focused on machine learning implementations in production environments.
• Strong software engineering foundation withexpertisein Python and SQL as well as experience with at least oneadditionallanguage (Go, Rust, Java, or JVM-family languages).
• Demonstrated experience building and deploying ML systems using modern frameworks and libraries (scikit-learn,PyTorch, TensorFlow,HuggingFace, or similar).
• Experience with LLMs, retrieval‑augmented generation (RAG), or advanced NLP techniques is beneficial.
• Proventrack recordimplementing ML solutions such as classification systems, time series analysis, anomaly detection, or NLP applications that deliver measurable business impact.
• Experience withMLOpspractices, including model versioning, monitoring, pipeline orchestration, and deployment in high-reliability environments.
• Familiarity with data engineering concepts, including data pipelines, stream processing, message queuing, and working with medium-to-large scale datasets.
• Knowledge of containerized deployment solutions and cloud-native architectures.
• Strong communicationskills with the ability to explain technical concepts to diverse stakeholders and collaborate effectively across teams.
• Cybersecurity domain knowledge, particularly in threat detection, threat intelligence, orICS/OT operations.

Responsibilities

• Design and implement production‑grade machine learning systems that expand Dragos product capabilities, with consideration for both cloud and resource‑constrained on‑premises environments.
• Build andoptimizeML model architectures for IC/OT cybersecurity use cases, including threat detection, asset classification, behavioral analysis, anomaly detection, and natural language processing systems.
• Develop robust data pipelines and ML workflows that integrate with existing data infrastructure, supporting both real‑time and batch processing requirements.
• Collaborate withOT detection expertsto translate research concepts and prototypes into scalable, production‑ready ML systems.
• Partner with Data Engineers toestablishdata contracts and implement observability frameworks for ML pipelines, including monitoring, versioning, anddeploymentbest practices.
• Contribute to ML infrastructure improvements, including automated testing frameworks, CI/CD pipelines, and deployment strategies for containerized environments (Kubernetes, Docker).
• Evaluate and adaptstate‑of‑the‑artML research and open‑source models to domain‑specific cybersecurity applications.
• Troubleshoot andoptimizeML model performance in production environments, addressing issues related to latency, accuracy, andresourceutilization.

Skills

Python

SQL

Go

ML in production

Tools

scikit-learn

PyTorch

TensorFlow

HuggingFace

Kubernetes

Docker

Job description

Dragos seeks a Staff Machine Learning Engineer to design and deploy production ML systems within the Dragos platform, collaborating with Data Engineers and product teams to advance threat detection and security analysis for ICS/OT applications.

You will build ML solutions including classification, time‑series analysis, anomaly detection, and NLP, applying MLOps, CI/CD, and containerized deployments in Kubernetes and Docker. Remote work with global reach is supported.