Palo Alto Networks

Principal Machine Learning Platform Engineer (Prisma AIRS)

Palo Alto Networks$157K — $254K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • BS/MS or Ph.D. in Computer Science or related field, or equivalent experience
  • Extensive experience in software engineering with focus on MLOps and production ML models
  • Expert-level Python programming; additional languages like Go, Java, or C++ preferred
  • Hands-on experience building large-scale distributed systems in cloud environments
  • Proven leadership in ML systems architecture and MLOps pipelines using Kubernetes and Docker
  • Mastery in ML frameworks (e.g., TensorFlow, PyTorch) and inference optimization tools (e.g., ONNX, TensorRT)
  • Expertise in modern LLM inference engines and previous open-source contributions in this space is a plus.

Responsibilities

  • Lead architectural design of highly scalable, low-latency ML inference platform
  • Provide technical leadership and mentorship to team members
  • Drive performance optimization strategies for models and systems
  • Establish and enforce engineering standards for automated model deployment
  • Act as a technical liaison with principal engineers and product leaders
  • Resolve complex and ambiguous challenges in large-scale inference
  • Lead projects addressing novel security threats and performance goals.

Benefits

  • Opportunities for immigration sponsorship
  • Collaborative environment fostering innovation
  • Impactful role in shaping cutting-edge AI security solutions
  • Mentorship opportunities within an expert team
  • Access to leading technologies and resources in AI and security.
Full Job Description
Job Summary

Your Career
With Prisma AIRS, Palo Alto Networks is building the world's most comprehensive AI security platform. Organizations are increasingly building complex ecosystems of AI models, applications, and agents, creating dynamic new attack surfaces with risks that traditional security approaches cannot address. In response, Prisma AIRS delivers model security, posture management, AI red teaming, and runtime protection. Our customers can confidently deploy AI-driven innovation while ensuring a formidable security posture from development through runtime.
As a Principal Machine Learning Inference Engineer, you will serve as a technical authority and visionary for the Prisma AIRS team. You will be responsible for the architectural design and long-term strategy of our AI platform - ML inference. Beyond individual contribution, you will lead complex technical projects, mentor senior engineers, and set the standard for performance, scalability, and engineering excellence across the organization. Your decisions will have a profound and lasting impact on our ability to deliver cutting-edge AI security solutions at a massive scale.

Your Impact
Architect and Design: Lead the architectural design of a highly scalable, low-latency, and resilient ML inference platform capable of serving a diverse range of models for real-time security applications.

Technical Leadership: Provide technical leadership and mentorship to the team, driving best practices in MLOps, software engineering, and system design.

Strategic Optimization: Drive the strategy for model and system performance, guiding research and implementation of advanced optimization techniques like custom kernels, hardware acceleration, and novel serving frameworks.

Set The Standard: Establish and enforce engineering standards for automated model deployment, robust monitoring, and operational excellence for all production ML systems.

Cross-Functional Vision: Act as a key technical liaison to other principal engineers, architects, and product leaders to shape the future of the Prisma AIRS platform and ensure end-to-end system cohesion.

Solve the Hardest Problems: Tackle the most ambiguous and challenging technical problems in large-scale inference, from mitigating novel security threats to achieving unprecedented performance goals.

Qualifications

Your Experience
BS/MS or Ph.D. in Computer Science, a related technical field, or equivalent practical experience.

Extensive professional experience in software engineering with a deep focus on MLOps, ML systems, or productionizing machine learning models at scale.

Expert-level programming skills in Python are required; experience in a systems language like Go, Java, or C++ is nice to have.

Deep, hands-on experience designing and building large-scale distributed systems on a major cloud platform (GCP, AWS, Azure, or OCI).

Proven track record of leading the architecture of complex ML systems and MLOps pipelines using technologies like Kubernetes and Docker.

Mastery of ML frameworks (TensorFlow, PyTorch) and extensive experience with advanced inference optimization tools (ONNX, TensorRT).

A strong understanding of popular model architectures (e.g., Transformers, CNNs, GNNs) is a significant plus.

Demonstrated expertise with modern LLM inference engines (e.g., vLLM, SGLang, TensorRT-LLM) is required. Open-source contributions in these areas are a significant plus.

Experience with low-level performance optimization, such as custom CUDA kernel development or using Triton Language, is a plus.

Experience with data infrastructure technologies (e.g., Kafka, Spark, Flink) is great to have.

Familiarity with CI/CD pipelines and automation tools (e.g., Jenkins, GitLab CI, Tekton) is a plus.

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/com-missioned roles) is expected to be the annual range listed below. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here.

$157,200.00 - $254,100.00/yr

Is role eligible for Immigration Sponsorship?: Yes

About Palo Alto Networks

Palo Alto Networks, Inc. is an American multinational cybersecurity company with headquarters in Santa Clara, California. Its core products are a platform that includes advanced firewalls and cloud-based offerings that extend those firewalls to cover other aspects of security. The company serves over 70,000 organizations in over 150 countries, including 85 of the Fortune 100. It is home to the Unit 42 threat research team and hosts the Ignite cybersecurity conference.
Learn more about Palo Alto Networks
Size
11,870 employees
Market Cap
$42.6 billion
Industry
Net Income
-$368.2 million
Founded
2005
5 Year Trend
+25.7%
Revenue
$3.7 billion
NASDAQ

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