Dragos
Remote, Oregon
At Dragos, the mission is personal. The systems we protect deliver the water you drink, power your home, and keep the hospitals your community depends on running. Those critical infrastructure systems that power our civilization around the world are under attack every day by adversaries. When those systems fail, people are immediately at risk. We are the global leader in xOT cybersecurity, combining technology, threat intelligence, and expert services. The people here chose this work because they understand what is at stake. Here, you will find a remote-first mission-driven team across North America, Europe, the Middle East, and APAC built on authenticity, transparency, and trust. If safeguarding the systems that protect your family, friends, and community is the kind of work that matters to you, you are in the right place. About the Role : Dragos is seeking a highly skilled Senior Software Engineer to join our Vulnerability Analysis content team. The ideal candidate will play a pivotal role in accelerating the delivery of vulnerability findings to our customers through robust automation and tooling. Collaborating closely with our team of vulnerability analysts, this person will be responsible for designing, building, and maintaining the CI/CD pipeline that powers our analysis review and deployment workflows. This critical function supports the rapid and accurate dissemination of vulnerability intelligence to protect operational technology (OT) environments. Responsibilities : Design, build, and maintain CI/CD pipelines for content review, validation, and deployment, including vulnerability analysis, asset catalogs, and report generation. Develop and improve analyst workflows and tooling to streamline the vulnerability analysis and publication process. Partner with vulnerability analysts to understand pain points and automate repetitive tasks in the content creation lifecycle. Implement automated testing frameworks, including unit, integration, and end-to-end tests for vulnerability content validation. Implement and maintain data validation, schema enforcement, and content quality assurance automation to ensure accuracy and consistency of vulnerability findings. Collaborate with other engineering teams to integrate vulnerability content delivery into broader Dragos systems. Mentor junior engineers and guide best practices. Continuously improve deployment velocity and content quality. Qualifications : 5+ years in a production software development environment, with 2+ years of experience with Python development. 1+ years of experience designing and maintaining CI/CD pipelines using tools such as Jenkins, GitLab CI, GitHub Actions, or similar. Experience with containerization technologies (Docker, Kubernetes) and infrastructure-as-code (Terraform, Ansible, or similar). Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native services. Demonstrated ability to design and build developer tooling and workflow automation that improves team productivity. Proficiency with git workflows, branching strategies, and code review processes at scale. Solid understanding of Linux systems administration and command-line tooling. Strong communication skills with the ability to translate technical concepts for non-technical stakeholders. Experience working in a security-focused environment or with security content delivery pipelines is a plus. ICS/OT knowledge and experience is nice to have. Rust knowledge and experience is nice to have. Experience with observability tools (Prometheus, Grafana, ELK stack, or similar) is helpful. Background in vulnerability management, threat intelligence, or security operations is a bonus. Compensation : Salary: $165,000 Competitive Equity Package Comprehensive Benefits Plan Dragos is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, state, or local laws. All new hires must pass a background check as a condition of employment.
At Dragos, the mission is personal. The systems we protect deliver the water you drink, power your home, and keep the hospitals your community depends on running. Those critical infrastructure systems that power our civilization around the world are under attack every day by adversaries. When those systems fail, people are immediately at risk. We are the global leader in xOT cybersecurity, combining technology, threat intelligence, and expert services. The people here chose this work because they understand what is at stake. Here, you will find a remote-first mission-driven team across North America, Europe, the Middle East, and APAC built on authenticity, transparency, and trust. If safeguarding the systems that protect your family, friends, and community is the kind of work that matters to you, you are in the right place. About the Role : Dragos is seeking a highly skilled Senior Software Engineer to join our Vulnerability Analysis content team. The ideal candidate will play a pivotal role in accelerating the delivery of vulnerability findings to our customers through robust automation and tooling. Collaborating closely with our team of vulnerability analysts, this person will be responsible for designing, building, and maintaining the CI/CD pipeline that powers our analysis review and deployment workflows. This critical function supports the rapid and accurate dissemination of vulnerability intelligence to protect operational technology (OT) environments. Responsibilities : Design, build, and maintain CI/CD pipelines for content review, validation, and deployment, including vulnerability analysis, asset catalogs, and report generation. Develop and improve analyst workflows and tooling to streamline the vulnerability analysis and publication process. Partner with vulnerability analysts to understand pain points and automate repetitive tasks in the content creation lifecycle. Implement automated testing frameworks, including unit, integration, and end-to-end tests for vulnerability content validation. Implement and maintain data validation, schema enforcement, and content quality assurance automation to ensure accuracy and consistency of vulnerability findings. Collaborate with other engineering teams to integrate vulnerability content delivery into broader Dragos systems. Mentor junior engineers and guide best practices. Continuously improve deployment velocity and content quality. Qualifications : 5+ years in a production software development environment, with 2+ years of experience with Python development. 1+ years of experience designing and maintaining CI/CD pipelines using tools such as Jenkins, GitLab CI, GitHub Actions, or similar. Experience with containerization technologies (Docker, Kubernetes) and infrastructure-as-code (Terraform, Ansible, or similar). Experience with cloud platforms (AWS, Azure, or GCP) and cloud-native services. Demonstrated ability to design and build developer tooling and workflow automation that improves team productivity. Proficiency with git workflows, branching strategies, and code review processes at scale. Solid understanding of Linux systems administration and command-line tooling. Strong communication skills with the ability to translate technical concepts for non-technical stakeholders. Experience working in a security-focused environment or with security content delivery pipelines is a plus. ICS/OT knowledge and experience is nice to have. Rust knowledge and experience is nice to have. Experience with observability tools (Prometheus, Grafana, ELK stack, or similar) is helpful. Background in vulnerability management, threat intelligence, or security operations is a bonus. Compensation : Salary: $165,000 Competitive Equity Package Comprehensive Benefits Plan Dragos is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, state, or local laws. All new hires must pass a background check as a condition of employment.
Dragos
Remote, Oregon
At Dragos, the mission is personal. The systems we protect deliver the water you drink, power your home, and keep the hospitals your community depends on running. Those critical infrastructure systems that power our civilization around the world are under attack every day by adversaries. When those systems fail, people are immediately at risk. We are the global leader in xOT cybersecurity, combining technology, threat intelligence, and expert services. The people here chose this work because they understand what is at stake. Here, you will find a remote-first mission-driven team across North America, Europe, the Middle East, and APAC built on authenticity, transparency, and trust. If safeguarding the systems that protect your family, friends, and community is the kind of work that matters to you, you are in the right place. About the Role We're looking for a Machine Learning Application Engineer to join our Engineering team. This role sits at the intersection of data engineering and applied ML. You'll be taking existing model types and putting them to work inside our product and data pipelines. You won't be training models from scratch or managing ML infrastructure, but you will be doing the thoughtful applied work of figuring out which techniques fit which problems, wiring them into our workflows, and making sure the outputs are reliable and useful. You'll work closely with AI Engineers, Data Engineers, and product teams to bring ML-driven capabilities into the Dragos platform. Things like clustering network behaviors, classifying assets, and surfacing anomalies that matter for ICS/OT security analysts. 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. Write clean, maintainable Python or Rust that other engineers can reason about, test, and extend. Troubleshoot ML component behavior in production to diagnose issues with output quality, data drift, or unexpected edge cases. Communicate clearly about what a model is doing, where it's uncertain, and how its outputs should (and shouldn't) be used downstream. Qualifications 5+ 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. Ability to evaluate whether a model's outputs are actually trustworthy for a given use case - not just whether accuracy metrics look good. Strong written and verbal communication; comfortable explaining tradeoffs to both technical and non-technical stakeholders. Nice to Have Cybersecurity domain knowledge - especially around threat detection, network behavior, or ICS/OT operations is a meaningful plus, but not a prerequisite. Experience working with graph-based representations of network topology or asset relationships. Familiarity with stream processing or event-driven architectures. Exposure to containerized environments (Docker, Kubernetes) as a consumer/deployer, not necessarily an operator. Compensation : Salary: $190,000 Competitive Equity Package Comprehensive Benefits Plan Dragos is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, state, or local laws. All new hires must pass a background check as a condition of employment.
At Dragos, the mission is personal. The systems we protect deliver the water you drink, power your home, and keep the hospitals your community depends on running. Those critical infrastructure systems that power our civilization around the world are under attack every day by adversaries. When those systems fail, people are immediately at risk. We are the global leader in xOT cybersecurity, combining technology, threat intelligence, and expert services. The people here chose this work because they understand what is at stake. Here, you will find a remote-first mission-driven team across North America, Europe, the Middle East, and APAC built on authenticity, transparency, and trust. If safeguarding the systems that protect your family, friends, and community is the kind of work that matters to you, you are in the right place. About the Role We're looking for a Machine Learning Application Engineer to join our Engineering team. This role sits at the intersection of data engineering and applied ML. You'll be taking existing model types and putting them to work inside our product and data pipelines. You won't be training models from scratch or managing ML infrastructure, but you will be doing the thoughtful applied work of figuring out which techniques fit which problems, wiring them into our workflows, and making sure the outputs are reliable and useful. You'll work closely with AI Engineers, Data Engineers, and product teams to bring ML-driven capabilities into the Dragos platform. Things like clustering network behaviors, classifying assets, and surfacing anomalies that matter for ICS/OT security analysts. 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. Write clean, maintainable Python or Rust that other engineers can reason about, test, and extend. Troubleshoot ML component behavior in production to diagnose issues with output quality, data drift, or unexpected edge cases. Communicate clearly about what a model is doing, where it's uncertain, and how its outputs should (and shouldn't) be used downstream. Qualifications 5+ 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. Ability to evaluate whether a model's outputs are actually trustworthy for a given use case - not just whether accuracy metrics look good. Strong written and verbal communication; comfortable explaining tradeoffs to both technical and non-technical stakeholders. Nice to Have Cybersecurity domain knowledge - especially around threat detection, network behavior, or ICS/OT operations is a meaningful plus, but not a prerequisite. Experience working with graph-based representations of network topology or asset relationships. Familiarity with stream processing or event-driven architectures. Exposure to containerized environments (Docker, Kubernetes) as a consumer/deployer, not necessarily an operator. Compensation : Salary: $190,000 Competitive Equity Package Comprehensive Benefits Plan Dragos is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics, or any other basis forbidden under federal, state, or local laws. All new hires must pass a background check as a condition of employment.