Principal Machine Learning Engineer (AI-ML Data Scientist - ADEM)

Palo Alto Networks • Santa Clara, CA

5d • $163,200 - $264,000 • Onsite

About The Position

Palo Alto Networks’ ADEM group is seeking a Principal AI-ML / Data Scientist to serve as a principal technical anchor for its next-generation AIOps platform. The role bridges advanced AI research and production-grade backend engineering, transforming large volumes of system telemetry into autonomous, self-healing capabilities.

The position leads technical design of intelligent, agentic workflows and contributes to a core backend rearchitecture. It is suited to a hands-on technical leader who builds advanced reasoning systems, optimizes large-scale data foundations, and mentors engineering teams. The role emphasizes delivering scalable, reliable, safe, observable, and high-performance solutions from prototype through production. Palo Alto Networks states that most teams work from the office full time, with flexibility when needed.

Requirements

• At least 8 years of software engineering experience, including a track record of deploying production-grade ML, GenAI, or agentic workflows at scale.
• Strong Python skills for AI/ML and professional experience with Go or Java for backend microservices.
• Hands-on experience with SQL, designing and restructuring BigQuery schemas, and building or managing scalable data pipelines using Dataflow, Google ADK, and GKE.
• Understanding of retrieval systems (RAG), prompt engineering, model evaluation, and statistical modeling.
• Ability to build platform-level services that integrate with adjacent ecosystems such as Prisma Access and Cortex.
• BS or MS in Computer Science, Data Science, Engineering, or a related field.

Nice To Haves

• Knowledge of L3-L7 networking is desirable.

Responsibilities

• Lead the design and implementation of ML-, LLM-, and GenAI-powered agents capable of planning, multi-step execution, self-correction, and collaboration with humans or other agents.
• Build reasoning pipelines, retrieval systems (RAG), and knowledge graph integrations for autonomous task execution and network troubleshooting.
• Build, fine-tune, or adapt LLMs, multimodal models, and specialized agent models, integrating traditional AI/ML and statistical models into agentic workflows for complex endpoint telemetry.
• Drive solution development from prototype to production, ensuring scalability, reliability, safety, observability, and performance.
• Establish best practices for prompt design, agent memory management, tool use, and context optimization.
• Evaluate emerging agent frameworks, LLM tooling, and generative AI technologies to inform platform architecture and roadmap decisions.
• Mentor engineering teams and contribute to the core backend rearchitecture.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal