below marketmost similar roles pay hereabove market
This role pays more than
96%
of similar roles. Most pay
$198,000–$254,750
— the blue band above.
At the midpoint, this role pays about
$336k
versus about
$226k
for comparable roles.
Based on 240 similar postings.
Employer
About Cisco
Cisco Systems is the world''s leading networking technology company, designing and manufacturing networking hardware, telecommunications equipment, and cybersecurity solutions for businesses and governments. Industry: Networking Technology & Cybersecurity
Cisco currently has
307 open roles
on FindRole.
Listed pay typically runs
$167,700–$245,000
across 224 roles with salary data.
The Principal Machine Learning Engineer joins the AI Software & Platform Team to serve as a lead technical architect for the Agentic Ops Solution. In this role, you will define the architectural vision, lead system design, and direct technical execution for AI platform capabilities. You will build shared infrastructure, abstractions, and paved roads to enhance engineering productivity. Key responsibilities include developing LLM and agentic systems featuring orchestrators, ReAct-style agents, tool calling, and MCP servers. You will utilize Python, Go, or TypeScript/Node.js alongside Kubernetes, Docker, and cloud hyperscaler platforms. The work involves solving complex problems in security resilience, threat defense, and operational automation by connecting enterprise product dashboards with intelligent, agentic AI capabilities across both SaaS and on-premise deployment models.
What does a Machine Learning Engineer earn in California?
Median $235750 from 200 postings across 34 companies.
Define the architectural vision and lead system design for the Agentic Ops Solution.
Direct technical execution and establish engineering standards for scalable AI platform capabilities.
Build shared infrastructure, abstractions, and "paved roads" to enhance productivity across engineering teams.
Develop LLM and agentic systems including orchestrators, tool calling, and asynchronous task results.
Manage service deployments on Kubernetes, including configuration, secret management, and health checks.
Perform cross-boundary debugging using logs, traces, and metrics to ensure system reliability.
Lead design reviews and provide technical mentorship to engineers across cross-functional boundaries.
What we're looking for
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related field with 12+ years of software engineering experience.
Master’s degree with 10+ years of experience or PhD with 7+ years of experience is also accepted.
Minimum of 8 years of experience designing and deploying distributed cloud software platforms, microservices, or enterprise-scale automation systems.
Minimum of 4 years of experience in a technical leadership capacity driving architectural decisions across multi-disciplinary engineering teams.
Demonstrated experience building and deploying production applications utilizing Generative AI, LLM orchestration frameworks, or AI assistants/copilots.
Hands-on experience developing backend or full-stack software using Python, Go, or TypeScript/Node.js and cloud-native technologies like Kubernetes and Docker.