Dragos

1 month ago

Staff ML Application Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 29 minutes agoStatus: Live

Job Summary

Join a remote-first, security-focused engineering team to operationalize ML within the Dragos platform. You’ll apply clustering, classification, and anomaly detection to ICS/OT cybersecurity data, integrate ML outputs into data pipelines and product workflows, and translate research into reliable pipeline components. Collaborate with AI/Data Engineers and product teams to surface meaningful ML-driven capabilities for security analysts.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•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, supporting both batch and near-real-time processing patterns.
•Understand model behavior and translate research outputs into reliable pipeline components.
•Work with Data Engineers to ensure ML-driven stages of the pipeline have clear data contracts, appropriate observability, and sane failure modes.
•Evaluate open-source and third-party models for fit against specific use cases, knowing when to apply an existing tool versus when to escalate to a model-building effort.

Pay and Benefits

Salary: USD 225,000

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•4+ 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; you don’t need to have implemented a neural net, but you should know how to use one responsibly.
•Solid understanding of data pipeline concepts: how data flows, where it gets transformed, what can go wrong, and how to make failures visible.

Experience:4+ yearsCybersecurityICS/OTData pipelinesML outputs

Skills:CommunicationProblem-solvingCollaboration

Languages:English

Tech Stack:PythonRustSQLScikit-learnDockerKubernetes

Company Brief

Dragos

Provides industrial cybersecurity solutions protecting operational technology (OT) and industrial control systems (ICS) with threat detection, incident response, and asset visibility to secure critical infrastructure and manufacturing environments.

Industry: Cybersecurity

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: Washington, D.C., United States

Founded: 2016

Website LinkedIn

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Dragos

1 month ago

Staff ML Application Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 29 minutes agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•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, supporting both batch and near-real-time processing patterns.
•Understand model behavior and translate research outputs into reliable pipeline components.
•Work with Data Engineers to ensure ML-driven stages of the pipeline have clear data contracts, appropriate observability, and sane failure modes.
•Evaluate open-source and third-party models for fit against specific use cases, knowing when to apply an existing tool versus when to escalate to a model-building effort.

Pay and Benefits

Salary: USD 225,000

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•4+ 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; you don’t need to have implemented a neural net, but you should know how to use one responsibly.
•Solid understanding of data pipeline concepts: how data flows, where it gets transformed, what can go wrong, and how to make failures visible.

Experience:4+ yearsCybersecurityICS/OTData pipelinesML outputs

Skills:CommunicationProblem-solvingCollaboration

Languages:English

Tech Stack:PythonRustSQLScikit-learnDockerKubernetes

Company Brief

Dragos

Industry: Cybersecurity

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: Washington, D.C., United States

Founded: 2016

Website LinkedIn