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Strong employer brand plus metro location and mid-level ML role increase applicant competition moderately.
Role requires ML plus cybersecurity domain expertise, reducing cross-industry transferability significantly.
Explicit 5–9 years requirement and specialized AI/cybersecurity MLOps skills create high filtering rigidity.
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Develop and implement AI-driven models and agentic AI solutions to detect cybersecurity threats and improve security posture.
Design and build AI agents and multi-agent workflows for automated threat detection, alert triage, incident investigation, vulnerability analysis, and response orchestration.
Collaborate with data engineers and cybersecurity teams to deploy scalable, production-ready AI security analytics pipelines and automate security operations.
Master’s degree OR Bachelor’s degree with 5 to 9 years experience with analytic software tools/languages (e.g., SAS, SPSS, R, Python).
Experience applying generative AI and agent-based systems to cybersecurity use cases such as automated threat detection and security analysis.
Strong foundation in machine learning algorithms, statistical techniques including regression, clustering, classification, and hypothesis testing.
Work Experience Required: 5 to 9 years relevant experience.
Experience designing and deploying AI solutions specifically in cybersecurity environments focused on automation and threat response.
Proficiency in Python and ML/AI/agent development frameworks like TensorFlow, PyTorch, LangChain, LlamaIndex, or similar.
Familiarity with cloud platforms (AWS, Azure, Google Cloud), MLOps, and agile/product team environments.