Principal Machine Learning Developer

Role overview

Responsibilities

• Define AI-native platform architectures for observability, assurance, incident intelligence, threat analysis, optimization, and automation.
• Integrate LLMs and agentic workflows with operational network and security data.
• Build capabilities for anomaly detection, root-cause analysis, prediction, triage, threat investigation, and guided remediation.
• Develop operational world models and closed-loop automation for safe remediation.
• Build large-scale telemetry and event pipelines; apply RAG and grounding methods for reliable operator assistants.
• Develop cloud-native capabilities and drive architecture, experimentation, production deployment, reliability, and scale.
• Partner with product and engineering teams to deliver customer-facing products; lead and mentor engineers and researchers.

Minimum qualifications

• Bachelor’s degree with 12+ years of related experience, master’s degree with 7+ years, or PhD with 5+ years.
• 12+ years in AI/ML, platform engineering, distributed systems, agentic applications in networking, security operations, or related fields.
• Experience with large-scale operational data such as metrics, logs, events, alerts, traces, topology, configurations, and unstructured data.
• Programming experience in one or more of C++, Go, Java, or Python.

Preferred qualifications

• Experience applying agentic AI to network operations, security operations, or autonomous infrastructure.
• Knowledge of networking and SecOps platforms, security analytics, SIEM/SOAR, identity signals, vulnerability intelligence, or cloud security operations.
• Experience with multimodal learning, world models, graph ML, causal inference, RAG, or time-series modeling.
• Product mindset and experience taking cross-functional research and concepts through production.
• Published research, patents, or technical leadership in AI, networking, security, or distributed systems.
• Experience with real-time inference, anomaly detection, threat analysis, cloud-native distributed systems, Kubernetes, microservices, or multi-cloud platforms.

Compensation

• The posted starting salary range for the U.S. and/or Canada is CAD 228,700–289,000, excluding incentive compensation, equity, and benefits.
• Pay depends on hiring location, market conditions, job-related skills, experience, qualifications, education, certifications, and training.

Application timing