Dragos
Staff AI/ML Engineer
United States · Staff+
Sponsorship not specifiedDetected 1 day ago
PythonJavaGoRustSQLDockerKubernetesCI/CDMachine LearningTensorFlowPyTorchscikit-learnData EngineeringNLPLLMsRAGMLOpsCybersecurityDetection EngineeringTest AutomationResearch
About the role
- We're seeking an experienced Staff Machine Learning Engineer to join our Engineering team.
Responsibilities
- Build and optimize ML model architectures for ICS/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.
- Troubleshoot and optimize ML model performance in production environments, addressing issues related to latency, accuracy, and resource utilization.
- The systems we protect deliver the water you drink, power your home, and keep the hospitals your community depends on running.
Requirements
- Strong software engineering foundation with expertise in Python and SQL as well as experience with at least one additional language (Go, Rust, Java, or JVM-family languages).
- Experience with LLMs, retrieval-augmented generation (RAG), or advanced NLP techniques is beneficial.
- 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. <span data-ccp-props="{"134233117":true,"134233118":true,
- 6+ years of engineering experience with at least 4 years focused on machine learning implementations in production environments.
- Demonstrated experience building and deploying ML systems using modern frameworks and libraries (scikit-learn, PyTorch, TensorFlow, HuggingFace, or similar).
- Proven track record implementing ML solutions such as classification systems, time series analysis, anomaly detection, or NLP applications that deliver measurable business impact.
Benefits
- Design and implement production-grade machine learning systems that expand Dragos product capabilities, with consideration for both cloud and resource-constrained on-premises environments.
Company info
- We are the global leader in xOT cybersecurity, combining technology, threat intelligence, and expert services.
This listing is sourced directly from Dragos's careers page and normalized into a canonical job model.