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Armis, a ServiceNow cybersecurity company, is building an autonomous defense platform for the Agentic Enterprise. The platform combines Armis's asset and vulnerability management capabilities with ServiceNow's security and identity solutions to protect organizations' entire attack surfaces in real time. Machine Learning and Generative AI power the core detection, vulnerability management, and remediation (VMDR) capabilities.
You will join the VMDR team as a Staff Data Scientist, acting as a technical builder and owner of complex problem domains end-to-end. This is a high-impact individual contributor role where you will drive AI and ML initiatives through the full product lifecycle—from early-stage research and prototyping through production deployment and monitoring.
Key responsibilities:
- Own complex AI and ML initiatives end-to-end, from research through scalable production deployment
- Design and build production-ready AI models and system pipelines in Python using modern cloud and big data infrastructure (AWS, Spark)
- Integrate state-of-the-art Generative AI and LLM workflows into core VMDR features to drive automated detection, prioritization, and remediation
- Partner with domain researchers, data engineers, and product leaders to translate complex cybersecurity problems into high-impact AI solutions
- Stay ahead of emerging AI trends and take full ownership of problem domains in a collaborative, high-trust environment
Requirements:
- At least 2 years of hands-on experience with Large Language Models (LLMs), including prompt engineering, fine-tuning, RAG, agentic workflows, and orchestration frameworks (LangChain, LlamaIndex, vLLM, or similar)
- 5+ years of software development experience with strong, production-grade Python coding and experience deploying ML systems at scale
- Deep algorithmic and theoretical knowledge in Machine Learning, supported by an M.Sc. or Ph.D. (or equivalent research experience)
- Cybersecurity domain experience in Vulnerability Management, Asset Intelligence, or Threat Detection is advantageous but not required
- Self-driven, autodidactic approach with natural ability to take full ownership and thrive in collaborative team environments
