Sr. Staff Machine Learning Engineer

About the role

The Team Engineering at Palo Alto Networks is dedicated to developing robust, next-generation cloud security solutions. This role requires strong technical leadership, expertise in machine learning frameworks, and experience in designing and building large-scale, distributed systems on public cloud platforms.

Responsibilities

• Provide technical leadership for end-to-end solution delivery, collaborating with cross-functional teams 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.
• 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.

Qualifications

• 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

Preferred Qualifications

• 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

Pay

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 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. $141,000.00 - $228,750.00/yr

Our Commitment

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 accommodations@paloaltonetworks.com. 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