Staff Data Scientist (Armis/Veza)

Job description

Armis from ServiceNow, protects the entire attack surface and manages an organization’s cyber risk exposure in real time. Combined with ServiceNow’s Security and Risk capabilities, as well as Identity Security capabilities from Veza, we bring together all critical capabilities to secure every asset, every identity - incl. AI Agents - across all environments with the right level of context - security, operational and business - to build the first of its kind autonomous defense platform for the Agentic Enterprise.

As an AI-driven cybersecurity company, Machine Learning and Generative AI power the core capabilities that make Armis an industry leader. Our algorithms are the engine behind our advanced Vulnerability Management, Detection, and Remediation (VMDR) platform. We are looking for a Staff Data Scientist with strong Machine Learning foundations and practical enterprise experience to join the VMDR team. In this role, you will act as a technical builder owning complex problem domains end-to-end, diving deep into cybersecurity nuances, and architecting cutting-edge LLM and ML solutions from initial research all the way to scalable production deployment.

What You’ll Do

End-to-End Ownership: Drive complex AI and ML initiatives through the full product lifecycle from early-stage prototyping and deep domain analysis to production-grade deployment and monitoring.

Architect & Deploy

Design and build production-ready AI models and system pipelines in Python using modern cloud and big data infrastructure (AWS, Spark).

LLM Innovation

Integrate state-of-the-art Generative AI and LLM workflows directly into our core VMDR features to drive automated detection, prioritization, and remediation insights.

Domain Deep-Dives

Partner closely with domain researchers, data engineers, and product leaders to dive into granular cybersecurity data and translate complex security problems into high-impact AI solutions.

Qualifications

Cybersecurity Background

Domain experience in cybersecurity (specifically Vulnerability Management, Asset Intelligence, or Threat Detection) is a big advantage, but not mandatory.

LLM Expertise

At least 2 years of hands-on experience working with Large Language Models (LLMs), including prompt engineering, fine-tuning, RAG, agentic workflows, and orchestration frameworks (e.g., LangChain, LlamaIndex, vLLM, or similar).

Solid ML Foundations

Deep algorithmic and theoretical knowledge in Machine Learning, supported by an Academic Degree (M.Sc. or Ph.D. preferred) or equivalent research experience.

Production Engineering Skills

5+ years of software development experience, with strong, production-grade Python coding abilities and experience deploying ML systems at scale.

Self-Driven & Collaborative

An autodidact who naturally takes full ownership of problem domains, stays ahead of emerging AI trends, and thrives in a high-trust, collaborative team environment.