Principal AI/ML Engineer

Palo Alto Networks

1d•Onsite

About The Position

We are seeking a highly experienced Principal Software engineer with a good understanding of machine learning principles to join our team and drive the development of our Support Transformation. In this role, you will combine robust backend engineering expertise with machine learning expertise to build, deploy, and maintain a cutting-edge support system that enhances user experiences and operational efficiency.

Requirements

5+ years of experience using an Object–Oriented programming language (Java/Python)
Experience with cloud-native service development stack on GCP
Knowledge of Object Oriented Programming design concepts
Solid grasp of RESTful API design and micro services architecture.
Basic understanding of machine learning concepts and familiarity with ML frameworks (e.g., TensorFlow, PyTorch) is a plus.
Skilled in diagnosing and solving complex problems while providing detailed technical analysis
Attention to details and high behavioral standards
Team player with can-do attitude to tackle difficult problems and you inspire your team to do the same
High energy and the ability to work in a fast-paced environment
Excellent collaboration and communication with multiple teams
Fast learner and eager to absorb new emerging technologies
M.S./B.S. degree in Computer Science or Electrical Engineering or equivalent military experience

Responsibilities

Develop and maintain scalable backend systems and APIs that integrate seamlessly with machine learning components.
Architect and implement data pipelines to support efficient model training, validation, and real-time inference.
Collaborate with data scientists to deploy, monitor, and optimize AI prompts within the support pipeline.
Ensure smooth integration of ML solutions into production systems, focusing on performance, reliability, and scalability.
Build automation tools for continuous integration, delivery, and deployment of backend and ML components.
Implement monitoring and logging solutions to proactively address performance issues and ensure system reliability.
Work closely with cross-functional teams (product, QA, DevOps, and customer support) to align development efforts with business needs.
Troubleshoot and resolve complex issues that arise within both the backend infrastructure and ML models.
Ensure code quality, security, and data privacy by following industry best practices.
Maintain clear and concise documentation for system architecture, API endpoints, and ML model integration processes.