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Palo Alto Networks

Principal Machine Learning Engineer (Prisma AIRS)

Palo Alto Networks
Santa Clara, CA $163k - $264k/yr Full time Posted 18d ago
Ai Enabled Security Ai Security Artificial Intelligence Data Pipeline Data Processing Data Science Large Language Models Llm Security Machine Learning Machine Learning Leadership NLP Principal Machine Learning Engineer Programming Programming Language Programming Languages Security
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Job Description

Hybrid role in Santa Clara, CA with a senior technical scope on Palo Alto Networks’ Prisma AIRS team. You will help shape a new initiative focused on high-performance AI/ML infrastructure and autonomous runtime security capabilities to classify threats and reduce adversarial risk across enterprise environments.

Compensation range: USD 163,200 to 264,000 per year. The final offer depends on qualifications, experience, and work location, and may include restricted stock units and a bonus. Immigration sponsorship: Yes.

What you’ll work on

As a senior technical leader within AIRS (Artificial Intelligence Runtime Security), you will design and deploy infrastructure and ML solutions that operate at the intersection of machine learning, cloud security, and AI safety. The focus is on building scalable pipelines and autonomous model-driven capabilities that help prevent adversarial attacks at enterprise scale.

This is a brand-new initiative within the AIRS team, recruiting senior technical leaders to help drive the architecture from the ground up.

Responsibilities

  • Develop scalable anomaly detection pipelines to monitor cloud environments and AI agent actions, with an emphasis on strong efficacy and low false-positive and false-negative rates.
  • Lead SLM (Small Language Model) tuning initiatives, optimizing and fine-tuning models for low-latency, high-accuracy edge-cloud security tasks.
  • Drive advanced data classification strategies using machine learning, NLP, and deep learning to extract threat patterns from massive structured and unstructured datasets.
  • Partner closely with product, security, and cloud engineering teams to integrate ML solutions into production systems.

Requirements

  • MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related field (or equivalent practical experience).
  • 8+ years of software engineering industry experience, including 3+ years dedicated to machine learning, NLP, or AI systems.
  • Deep programming expertise in Python.
  • Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
  • Proven experience working directly with LLMs/SLMs, including advanced prompt engineering and model fine-tuning techniques.
  • Demonstrated experience building and scaling auto-classification and anomaly detection models on large, real-world datasets.
  • Knowledge of cybersecurity concepts and AI safety vulnerabilities, including areas such as prompt injection defense, AI red-teaming, and model security.
  • Familiarity with DistilBERT and other open-source classification models.
  • Familiarity with large, graph-based datasets and processing techniques.
  • Experience with distributed cloud systems (GCP or AWS) and deploying scalable ML inference pipelines at scale.

Tech you may work with

  • Python, PyTorch, TensorFlow
  • LLMs, SLMs, NLP
  • DistilBERT
  • GCP, AWS

Level and team

  • Levels considered: Sr. Staff and Principal Engineers
  • Team: AIRS (Artificial Intelligence Runtime Security)

Location

Santa Clara, CA (Hybrid: 3 days/week on-site at Corporate HQ)

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