Remote Staff ML Engineer - Cybersecurity AI Threat Detection

Dragos, Inc.; United States; On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Equity

Job summary

Dragos, Inc. is seeking a Staff Machine Learning Engineer to design and deploy production ML systems within the Dragos platform, collaborating with Data Engineers and product teams to enhance ICS/xOT threat detection and security analytics.

You will translate research into scalable, reliable solutions for real-world industrial environments. The role emphasizes MLOps, containerized deployment (Kubernetes, Docker), and cross‑functional collaboration to deliver measurable impact across cloud and

Qualifications

• 6+ years of engineering experience with at least 4 years focused on machine learning implementations in production environments.
• Strong software engineering foundation with Python and SQL as well as experience with at least one additional language (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.
• Proven track record implementing ML solutions such as classification systems, time‑series analysis, anomaly detection, or NLP applications that deliver measurable business impact.
• Experience with MLOps practices, 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 communication skills with the ability to explain technical concepts to diverse stakeholders and collaborate effectively across teams.
• Cybersecurity domain knowledge, particularly in threat detection, threat intelligence, or IC‑/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 and optimize ML 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 with OT detection experts to translate research concepts and prototypes into scalable, production‑ready ML systems.
• Partner with Data Engineers to establish data contracts and implement 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 issues related to latency, accuracy, and resource utilization.

Skills

Python

SQL

Go/Rust/Java

Tools

scikit-learn

PyTorch

TensorFlow

HuggingFace

Job description

Dragos, Inc. is seeking a Staff Machine Learning Engineer to design and deploy production ML systems within the Dragos platform, collaborating with Data Engineers and product teams to enhance ICS/xOT threat detection and security analytics.

You will translate research into scalable, reliable solutions for real-world industrial environments. The role emphasizes MLOps, containerized deployment (Kubernetes, Docker), and cross‑functional collaboration to deliver measurable impact across cloud and