# Principal Machine Learning Developer at Cisco

Cisco is hiring a Principal Machine Learning Developer for a remote role open to applicants in Canada. It pays $229k-$289k a year and Level rates it Little AI ●○○○; you can [apply on Level](https://jobsbylevel.com/go/998fabc4-3983-4932-b979-70fc7d58c03f?utm_medium=ai-agent).

AI Level 1, AI centrality 9 out of 100. Remote (Calgary, Alberta, Canada).

## Details

- Company: [Cisco](https://jobsbylevel.com/companies/cisco)
- AI level: AI Level 1 (score 9 out of 100)
- Location: Remote (Calgary, Alberta, Canada)
- Salary: $229k-$289k
- Posted: October 12, 2026
- Apply: https://jobsbylevel.com/go/998fabc4-3983-4932-b979-70fc7d58c03f?utm_medium=ai-agent

## Prepare for this job

The job page lists 3 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/principal-machine-learning-developer-at-cisco-aaf839

## Description

The application window is expected to close on: 11/15/2026 Meet the Team The Cisco CTO Organization is shaping the future of networking and security through AI-native, cloud-delivered, and autonomous operations platforms. We are investing in agentic AI to make network and security operations more observable, proactive, intelligent, and efficient at scale. Your Impact As a Principal Machine Learning Engineer Developer you will define how AI, LLMs, and autonomous operations transform network and security management across Cisco’s wireless, wired, cloud, enterprise networking, and security platforms! You will work at the intersection of networking, security operations, machine learning, large-scale telemetry, and agentic systems to enable faster diagnosis, proactive assurance, intelligent threat analysis, and safe automated remediation. Responsibilities: Define architectures for AI-native network and security operations platforms, spanning observability, assurance, incident intelligence, threat analysis, optimization, and automation Integrate LLMs and agentic workflows with network telemetry, topology, configurations, events, alerts, logs, and operational knowledge Build intelligent capabilities for anomaly detection, root-cause analysis, performance prediction, incident triage, threat investigation, and guided remediation Develop network and security world models that infer operational state across devices, users, services, applications, and dependencies Design closed-loop automation for proactive detection, intelligent investigation, policy recommendations, and safe remediation Build large-scale telemetry, time-series, graph, log, and event-processing pipelines to support real-time inference Apply RAG, domain adaptation, evaluation, and grounding techniques to create reliable AI assistants for network and security operators Develop cloud-native platform capabilities using Kubernetes, microservices, and multi-cloud architectures Drive end-to-end execution from architecture and experimentation through production deployment, reliability, and scale Partner with product and engineering teams to translate AI innovation into customer-facing networking and security operations products Lead and mentor engineers and researchers across AI, networking, security operations, cloud platforms, and distributed systems Minimum Qualifications: Bachelor's degree with 12+ years of related experience, Master's degree with 7+ years of related experience, or PhD with 5+ years of related experience. 12+ years in AI/ML, platform engineering, distributed systems, agentic applications in networking, security operations, or related fields Experience working with large-scale operational data, including metrics, logs, events, alerts, traces, topology, configurations, and unstructured data Experience with programming languages in C++, Go, Java, and/or Python Preferred Qualifications: Experience applying agentic AI to network operations, security operations, or autonomous infrastructure Deep knowledge of intent-based networking, closed-loop automation, self-driving networks, NaaS, SD-WAN, network observability, or SecOps platforms Experience with security analytics, SIEM/SOAR workflows, identity and access signals, vulnerability intelligence, or cloud security operations Experience with multimodal learning, world models, graph ML, causal inference, RAG, or time-series modeling Strong product mindset, connecting network and security operations innovation to customer outcomes and business value Experience driving cross-functional initiatives from research and concept through production Published research, patents, or demonstrated technical leadership in AI, networking, security, or distributed systems Experience with real-time inference, anomaly detection, root-cause analysis, threat analysis, or intelligent automation Experience designing cloud-native distributed systems, including Kubernetes, microservices, and multi-cloud platforms Experience with network

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/principal-machine-learning-developer-at-cisco-aaf839

Source: https://jobsbylevel.com/jobs/principal-machine-learning-developer-at-cisco-aaf839

## Cite this page

Level. https://jobsbylevel.com/jobs/principal-machine-learning-developer-at-cisco-aaf839.

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