Principal Machine Learning Platform Engineer (Prisma AIRS) at Palo Alto Networks

Santa Clara, California, United States -

Full Time

Start Date

Immediate

Expiry Date

15 Feb, 26

Salary

246500.0

Posted On

17 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Machine Learning, MLOps, Software Engineering, Python, Distributed Systems, Cloud Platforms, Kubernetes, Docker, TensorFlow, PyTorch, Inference Optimization, CUDA, CI/CD, Data Infrastructure, Performance Optimization, Model Architectures

Industry

Computer and Network Security

Description

Company Description Our Mission At Palo Alto Networks® everything starts and ends with our mission: Being the cybersecurity partner of choice, protecting our digital way of life. Our vision is a world where each day is safer and more secure than the one before. We are a company built on the foundation of challenging and disrupting the way things are done, and we’re looking for innovators who are as committed to shaping the future of cybersecurity as we are. Who We Are We take our mission of protecting the digital way of life seriously. We are relentless in protecting our customers and we believe that the unique ideas of every member of our team contributes to our collective success. Our values were crowdsourced by employees and are brought to life through each of us everyday - from disruptive innovation and collaboration, to execution. From showing up for each other with integrity to creating an environment where we all feel included. As a member of our team, you will be shaping the future of cybersecurity. We work fast, value ongoing learning, and we respect each employee as a unique individual. Knowing we all have different needs, our development and personal wellbeing programs are designed to give you choice in how you are supported. This includes our FLEXBenefits wellbeing spending account with over 1,000 eligible items selected by employees, our mental and financial health resources, and our personalized learning opportunities - just to name a few! At Palo Alto Networks, we believe in the power of collaboration and value in-person interactions. This is why our employees generally work full time from our office with flexibility offered where needed. This setup fosters casual conversations, problem-solving, and trusted relationships. Our goal is to create an environment where we all win with precision. Job Description 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. Additional Information The Team Our Prisma AIRS team is a group of highly motivated and innovative engineers and researchers dedicated to solving the most challenging problems in AI security. We thrive in a collaborative environment where we value creativity, ownership, and a commitment to excellence. You will have the opportunity to work with cutting-edge technology and make a significant impact on the future of cybersecurity. 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/commissioned roles) is expected to be between $151000/YR - $246500/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found here. Our Commitment We’re problem solvers that take risks and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at [email protected]. Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship?: Yes

Responsibilities

Lead the architectural design of a highly scalable ML inference platform and provide technical leadership to the team. Establish engineering standards for automated model deployment and operational excellence for production ML systems.