Principal Machine Learning Engineer (Prisma AIRS)

The Principal Machine Learning Engineer will serve as a senior technical leader on the AIRS (Artificial Intelligence Runtime Security) team within Prisma AIRS. In this role, you will design and deploy high-performance infrastructure and autonomous machine learning solutions that classify threats and help prevent adversarial attacks at enterprise scale.

Role Focus

You will operate at the intersection of machine learning, cloud security, and AI safety. Key work areas include anomaly detection pipelines, SLM tuning, data classification strategies, and the integration of ML systems into production environments.

Responsibilities

• Develop scalable anomaly detection pipelines to monitor cloud environments and AI agent actions, maintaining high efficacy with low false-positive and false-negative rates.
• Lead Small Language Model (SLM) tuning initiatives, optimizing and fine-tuning models for low-latency and high-accuracy edge-cloud security tasks.
• Drive advanced data classification strategies using machine learning, NLP, and deep learning to analyze massive structured and unstructured datasets and identify complex threat patterns.
• Act as a technical leader collaborating with product, security, and cloud engineering teams to integrate ML solutions into production systems.

Required Qualifications

• 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 at least 3 years focused on 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 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.

Technologies

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

About the Team

Palo Alto Networks is advancing the Prisma AIRS platform, which protects complex ecosystems of AI models, applications, and agents from development through runtime. This role supports a brand-new initiative within the AIRS team focused on state-of-the-art AI/ML infrastructure and high-performance, distributed backend systems. The search prioritizes senior technical leaders to help build the architecture from the ground up.

Location and Work Model

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

Experience Level Considered

• Sr. Staff Engineer
• Principal Engineer

Compensation

The compensation offered depends on qualifications, experience, and work location. For candidates receiving an offer at the posted level (non-sales roles), the starting base salary is expected to be within the annual range listed below. Compensation may also include restricted stock units and a bonus.

$163,200.00 - $264,000.00/yr

Immigration Sponsorship

Yes