PpNozomi Networks is the leader in OT and IoT cybersecurity, keeping the world's critical infrastructure cyber resilient through real-time asset visibility, threat detection, and AI‑powered analysis. We protect the toughest operational environments — from energy and healthcare to manufacturing and beyond. /p pAs a Senior Software Engineer in our Security Research department, you will work on cybersecurity projects focused on Threat Intelligence. You’ll be designing, implementing, and maintaining automation systems to support workflows related to threat detection and analysis. You’ll also collaborate with the team working on machine learning models and MLOps pipelines that power detection and analytics features. Collaborate with experienced engineers to build high-quality software using Python, UNIX-like scripting, and RDBMS technologies (experience with Golang will be a strong advantage). We prioritize clean code, automation, and continuous learning, offering opportunities for growth, training, and conference participation. If you’re passionate about threat intelligence, automation, machine learning engineering, and agile methodologies, this is the role for you. /p h3In This Role You Will /h3 ul liEmbody the Nozomi Networks Cultural Pillars and our mission to protect what matters most with transparency and trust /li liDevelop and maintain operations related to our Threat Intelligence infrastructure /li liDevelop automated systems to collect, share and correlate data related with cybersecurity threats to prevent attacks in critical infrastructures /li liDevelop ML models used in threat detection and classification use‑cases /li liContribute to MLOps workflows, including training automation, evaluation pipelines, model packaging, deployment support and observability of ML‑enabled systems /li /ul h3To Be Successful In This Opportunity, You Will Have /h3 ul liProven experience in Python or Golang software development /li liSoftware design knowledge. Design Patterns, SOLID, GRASP /li liHands‑on experience supporting ML systems in production and/or building MLOps pipelines (CI/CD, model versioning, reproducibility) /li liLove for simplicity. Writing clean and minimalist code, embracing the agile incremental approach /li liAutomated Testing experience (TDD, BDD, etc) /li liAttitude to operate in environments including data covered by non-disclosure agreements and high-level of confidentiality /li liDocker, AWS or Terraform are a plus /li liSolid foundations in machine learning and data‑driven development (model lifecycle, evaluation metrics, experimentation best practices) /li /ul /p #J-18808-Ljbffr