Staff Data Scientist
Reads like a ML Engineer role: putting models into production.
Tel Aviv, Israel
- Pay
- Pay not listed
- Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting
What you’ll work on
Full postingOwn complex AI and ML initiatives from prototype through production monitoring
Build production AI models and pipelines in Python on AWS and Spark
Integrate LLM and generative AI workflows into VMDR detection and remediation features
Work with researchers and engineers to turn granular security data into AI solutions
From the employer’s posting
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
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 directly into our core VMDR features to drive automated detection, prioritization, and remediation insights
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
Education & alternatives
- 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.
Tools in this posting
- Python
- AWS
- Spark
Source — Tool mentions in context
- 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.
- 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.
Posting record
Report an errorActively hiringFirst seen by us 10 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 19, 2026 · 10 days ago
- Recorded sightings
- 154
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
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
To be successful in this role you have:
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.
Additional Information
Work Personas
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.
Company Description
It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.
Join us to put AI to work for people.
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Tel Aviv, Israel
Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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