Principal Applied AI Researcher (Prisma AIRS)
$163.2k - $264kPaloAlto Networks
Our Mission At Palo Alto Networks , we're united by a shared mission-to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you're ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you're in the right place. Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! We believe collaboration thrives in person. That's why most of our teams work from the office full time, with flexibility when it's needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary Your Career As a Principal Applied AI Researcher on the Prisma AIRS Runtime Security team, you will serve as a technical visionary and strategic leader shaping the future of AI security. You will partner with executive leadership, product management, UX designers, ML engineers, and cross-functional engineering teams to conceptualize, architect, and deliver enterprise-grade, cutting-edge AI detection and protection solutions for the Prisma AIRS Runtime Security product. You will be at the vanguard of innovation for an industry-defining product in the rapidly evolving space of AI Runtime Security. Your responsibilities will transcend standard model development to lead continuous accuracy, latency, and efficiency optimizations, enabling high-throughput integrations across AI threat detection infrastructure, real-time guardrail pipelines, and partner engineering teams. You will drive technical excellence across the organization, set architectural and research standards, and act as a force multiplier by mentoring other researchers and engineers on the team. Your Impact
Your Experience
- Lead cross-functional collaboration with Product Management, ML, and Quality Engineering teams to deliver new, enterprise-grade AI security-as-a-service offerings in a timely, predictable fashion.
- Tackle complex, ambiguous technical challenges across system boundaries, translating high-level product and security vision into resilient, production-ready AI detection models and backend architectures.
- Design and select optimal AI architectures-from lightweight ML baselines to complex Transformers-to solve high-impact runtime security challenges.
- Train, fine-tune, and align domain-specific foundation models using modern techniques (PEFT, LoRA, DPO) and distributed training frameworks.
- Build scalable pipelines to filter, clean, and generate high-quality synthetic datasets for model training workflows.
- Develop automated benchmarks, LLM-as-a-judge evaluations, and real-time pipelines to monitor model accuracy, and drift in production.
- Develop models using techniques to minimize compute costs and meet strict, low-latency performance targets.
- Architect scalable model-serving infrastructure using high-throughput engines (vLLM, Triton) integrated into enterprise backend services.
- Mentor senior and junior engineers and researchers, fostering a culture of technical excellence, algorithmic rigor, and continuous learning within the team.
Your Experience
- 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience; or equivalent experience.
- Mastery of modern deep learning frameworks such as PyTorch and extensive hands-on experience with modern architectures (Transformers, LLMs).
- Proven experience with the modern LLM stack and a strong understanding of LLM guardrails and alignment techniques.
- Demonstrated history of successfully transitioning complex AI research or prototypes into high-throughput, low-latency production systems at scale.
- Advanced skills in Python and standard software engineering workflows, with experience deploying models using high-performance inference servers such as vLLM or Triton.
- Exceptional ability to distill complex statistical and architectural concepts for non-technical stakeholders and partner effectively with cross-functional executive leadership.
Vacancy posted 3 hours ago
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