Palo Alto Networks is building Prisma AIRS, an AI security platform designed to protect AI models, applications, and agents across the lifecycle, including development and runtime. This role supports a brand-new initiative within the AIRS (Artificial Intelligence Runtime Security) team, creating modern AI/ML infrastructure and high-performance distributed backend systems to classify threats and help prevent adversarial attacks at enterprise scale.
Working as a senior technical leader in Santa Clara, CA (hybrid, 3 days/week on-site at Corporate HQ), you will design and deploy autonomous ML solutions that combine anomaly detection pipelines, model tuning, and large-scale data classification. The work sits directly at the intersection of machine learning, cloud security, and AI safety.
What You’ll Do
- Develop scalable anomaly detection pipelines to monitor cloud environments and AI agent actions, targeting high efficacy with low false-positive and false-negative rates.
- Lead SLM (Small Language Model) tuning initiatives, optimizing fine-tuning and model behavior for low-latency, high-accuracy edge-cloud security tasks.
- Drive data classification strategies using machine learning, NLP, and deep learning across massive structured and unstructured datasets to extract complex threat patterns.
- Partner with product, security, and cloud engineering teams to integrate ML solutions into production systems.
What You Bring
- 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 focused on machine learning, NLP, or AI systems.
- Deep programming expertise in Python.
- Hands-on experience with deep learning frameworks including PyTorch or TensorFlow.
- Proven experience working with LLMs/SLMs, including advanced prompt engineering and model fine-tuning.
- Strong background building and scaling auto-classification and anomaly detection models on large, real-world datasets.
- Knowledge of cybersecurity concepts and AI safety vulnerabilities, 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.
Tools and Technologies
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)
Compensation and Sponsorship
Salary range: $163,200.00 - $264,000.00/yr. Compensation depends on qualifications, experience, and work location, and may include restricted stock units and a bonus. Immigration sponsorship: Yes.
