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Palo Alto Networks

Builds cybersecurity tools for organizations

Principal Applied AI Researcher

Applied Machine Learning +1Confirmed live in the last 24 hours
Full-timeSanta Clara, CA, USAIn-person

About the Job

Requirements

  • At least 8 years of related experience with a bachelor's degree, 6 years with a master's degree, or 3 years with a PhD; equivalent experience is accepted.
  • Mastery of modern deep learning frameworks such as PyTorch and extensive hands-on experience with modern architectures, including Transformers and large language models.
  • Proven experience with the modern large language model stack and a strong understanding of large language model guardrails and alignment techniques.
  • Demonstrated experience transitioning complex artificial intelligence research or prototypes into high-throughput, low-latency production systems at scale.
  • Advanced Python skills and standard software engineering workflow experience, including deploying models using high-performance inference servers such as vLLM or Triton.
  • Ability to explain complex statistical and architectural concepts to non-technical stakeholders and work effectively with cross-functional executive leadership.

Responsibilities

  • Lead cross-functional collaboration with Product Management, machine learning, and Quality Engineering teams to deliver enterprise-grade AI security-as-a-service offerings predictably and on time.
  • Address complex technical challenges across system boundaries and translate product and security vision into resilient, production-ready AI detection models and backend architectures.
  • Design and select AI architectures, from lightweight machine learning baselines to complex Transformers, for runtime security challenges.
  • Train, fine-tune, and align domain-specific foundation models using techniques such as PEFT, LoRA, and DPO, along with distributed training frameworks.
  • Build scalable pipelines to filter, clean, and generate high-quality synthetic datasets for model training workflows.
  • Develop automated benchmarks, large-language-model-as-a-judge evaluations, and real-time pipelines to monitor model accuracy and drift in production.
  • Develop models that minimize compute costs and meet strict low-latency performance targets.
  • Architect scalable model-serving infrastructure using high-throughput engines such as vLLM and Triton, integrated into enterprise backend services.
  • Mentor senior and junior engineers and researchers, fostering technical excellence, algorithmic rigor, and continuous learning within the team.

About the Company

Palo Alto Networks

Builds cybersecurity tools for organizations

Palo Alto Networks builds cybersecurity hardware and software for businesses and public institutions, protecting their networks, cloud workloads and digital identities. Its portfolio combines network firewalls with tools that detect attacks, investigate security alerts and manage access to sensitive systems. Security teams use these products across offices, data centers and cloud environments, with shared data and automated workflows connecting the company's platforms. It earns revenue from appliance sales and software licenses, plus subscriptions and support contracts that keep protections and services active over time. Palo Alto Networks began operations in 2005 and is headquartered in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
2005

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