Principal Machine Learning Engineer
About The Position
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 The Team Engineering - Our engineering team is at the core of our products and connected directly to the mission of preventing cyberattacks. We are constantly innovating — challenging the way we, and the industry, think about cybersecurity. Our engineers don’t shy away from building products to solve problems no one has pursued before. We define the industry instead of waiting for directions. We need individuals who feel comfortable in ambiguity, excited by the prospect of a challenge, and empowered by the unknown risks facing our everyday lives that are only enabled by a secure digital environment. Job Summary As a Principal Software Engineer, you will provide technical leadership in designing and delivering robust, next-generation cloud security solutions. You will drive the development of scalable cloud security architecture through hands-on coding, manage the full product lifecycle, and collaborate across teams to simplify complex technical issues and deliver high-quality security-as-a-service offerings. Security, Infrastructure & Optimization Design and implement robust, next-generation cloud security solutions to resolve complex backend infrastructure and ML model challenges. Strategically manage and optimize ML infrastructure and pipelines to improve performance, ensure smooth production integration, and reduce operational costs.
Requirements
- Strong background on machine learning and ML frameworks (e.g., TensorFlow, PyTorch)
- Experience with Infrastructure-as-Code (IaC) tools like Terraform or CloudFormation.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- 10+ years of software development experience, with a focus on cloud-native and SaaS applications.
- Proven experience in designing and building large-scale, distributed systems on public cloud platforms (AWS, GCP, Azure).
- Strong proficiency in at least one modern programming language such as Python, Go, or Java.
- Demonstrated experience with the full machine learning lifecycle, including model deployment and MLOps.
Nice To Haves
- Master's or PhD in Computer Science or a related technical field.
- Experience in the cybersecurity domain or with network security products.
- Expertise with containerization and orchestration technologies, particularly Docker and Kubernetes.
- Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink).
- Contributions to open-source projects in the cloud-native or MLOps space.
Responsibilities
- Provide technical leadership for end-to-end solution delivery, collaborating with cross-functional teams (Product, SRE, QA, and Support) to align engineering efforts with business objectives.
- Drive the development of scalable cloud security architecture through a balance of strategic planning and hands-on coding.
- Establish and evangelize best practices for model versioning, reproducibility, auditing, and compliance to ensure code quality and data privacy across the organization.
- Architect and lead the entire ML lifecycle, from initial development and training to production deployment and real-time inference.
- Build and maintain automated, resilient systems for continuous integration, delivery (CI/CD), and monitoring of backend and machine learning components.
- Continuously evaluate and integrate cutting-edge MLOps tools and frameworks to enhance system scalability, reliability, and efficiency.
Benefits
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
Associate degree
