# Principal AI Researcher, AISWP (Hybrid) at Cisco

- Company: Cisco
- What the company does: Cisco is a worldwide technology leader powering an inclusive future for all. Learn more about our products, services, solutions, and innovations. Backed by Sequoia and Menlo.
- Company website: https://www.cisco.com/
- Type: Startups (AI role)
- Level: Principal and up
- Location: 2 Locations
- Work setup: On-site
- Posted: 2026-09-01
- Apply by: 2026-10-16
- Apply: https://cisco.wd5.myworkdayjobs.com/en-US/Cisco_Careers/job/Seattle-Washington-US/Principal-AI-Researcher--AISWP--Hybrid-_2023217
- Page: https://www.1752.vc/careers/jobs/cisco-principal-ai-researcher-aiswp-hybrid/

## About the role

As a Principal AI Researcher, you will define the technical vision and overarching architecture for Cisco’s proprietary intelligence, serving as a primary catalyst for how we secure and automate the global network. Moving beyond leading individual projects, you will define the multi-year research strategy, pioneering novel approaches in foundation model development, agentic workflows, and self-improving systems.

## What they're looking for

- Bachelor’s degree in STEM with 15+ years of experience, a Master’s degree with 12+ years of experience, or a PhD in STEM or a related technical field with 8+ years of highly relevant research experience
- Experience architecting and leading multiple full-cycle pre-training, continual pre-training, or reinforcement learning pipelines for massive-scale foundational models, dictating dataset curation, distributed training strategies, and alignment execution
- Minimum of 6 publications in top-tier AI venues (ACL, EMNLP, ICLR, ICML, NAACL, NeurIPS), with a history of significant citations or influential contributions
- 5+ years of experience engineering and scaling training pipelines using PyTorch or similar frameworks on massive distributed computing environments (e.g., cluster environments using 1000+ GPUs)
- 4+ years of experience pioneering the application of generative ML models to highly complex, domain-specific systems such as networking, cybersecurity, or data center infrastructure
- Demonstrated experience defining the technical architecture for AI Developer Experiences, agentic frameworks, or autonomous troubleshooting agents deployed in production environments