Principal Engineer Machine Learning (MLOps DLP Detection)

Your Career

We are looking for a Principal MLOps Engineer to lead the design development and operation of production-grade machine learning this role you will architect robust pipelines deploy and monitor ML models and ensure reliability reproducibility and governance across our AI/ML ecosystem. You will work at the intersection of ML DevOps and cloud systems enabling our teams to accelerate experimentation while ensuring secure efficient and compliant deployments.

This role is located at our dynamic Santa Clara California headquarters campus and in office 3 days a week. Not a remote role.

Your Impact

• End-to-End ML Architecture and Delivery Ownership: Architect design and lead the implementation of the entire ML lifecycle. This includes ML model development and deployment workflows that seamlessly transition models from initial experimentation/development to complex cloud and hybrid production environments.
• Operationalize Models at Scale: Develop and maintain highly automated resilient systems that enable the continuous training rigorous testing deployment real-time monitoring and robust rollback of machine learning models in production ensuring performance meets massive scale demands.
• Ensure Reliability and Governance: Establish and enforce state-of-the-art practices for model versioning reproducibility auditing lineage tracking and compliance across the entire model inventory.
• Drive Advanced Observability & Monitoring: Develop comprehensive real-time monitoring alerting and logging solutions focused on deep operational health model performance analysis (e.g. drift detection) and business metric impact.
• Champion Automation & Efficiency: Act as the primary driver for efficiency pioneering best practices in Infrastructure-as-Code (IaC) sophisticated container orchestration and continuous delivery (CD) to reduce operational toil.
• Collaborate and Lead Cross-Functionally: Partner closely Security Teams and Product Engineering to define requirements and deliver robust secure and production-ready AI systems.
• Lead MLOps Innovation: Continuously evaluate prototype and introduce cutting-edge tools frameworks and practices that fundamentally elevate the scalability reliability and security posture of our production ML operations.
• Optimize Infrastructure & Cost: Strategically manage and optimize ML infrastructure resources to drive down operational costs improve efficiency and reduce model bootstrapping times.

Qualifications :

Your Experience 

• 8 years of software/DevOps/ML engineering experience with at least 3 years focused specifically on advanced MLOps ML Platform or production ML infrastructure and 5 yeas of experience building ML Models
• Deep expertise in building scalable production-grade systems using strong programming skills (Python Go or Java).
• Expertise in leveraging cloud platforms (AWS GCP Azure) and container orchestration (Kubernetes Docker) for ML workloads.
• Proven hands-on experience in the ML Infrastructure lifecycle including:
  • Model Serving: (TensorFlow Serving TorchServe Triton Inference Server/TIS).
  • Workflow Orchestration: (Airflow Kubeflow MLflow Ray Vertex AI SageMaker).
• Mandatory Experience with Advanced Inferencing Techniques: Demonstrable ability to utilize advanced hardware/software acceleration and optimization techniques such as TensorRT (TRT) Triton Inference Server (TIS) ONNX Runtime Model Distillation Quantization and pruning.
• Strong hands-on experience with comprehensive CI/CD pipelines infrastructure-as-code (Terraform Helm) and robust monitoring/observability solutions (Prometheus Grafana ELK/EFK stack).
• Comprehensive knowledge of data pipelines feature stores and high-throughput streaming systems (Kafka Spark Flink).
• Expertise in operationalizing ML models including model monitoring drift detection automated retraining pipelines and maintaining strong governance and security frameworks.
• A strong track record of influencing cross-functional stakeholders defining organizational best practices and actively mentoring engineers at all levels.
• Unwavering passion for operational excellence building highly scalable and securing mission-critical ML systems.
• MS/PhD in Computer Science/Data Science Engineering

Additional Information :

The Team

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 dont shy away from building products to solve the 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.

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  - $175000 - $220000/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

Were problem solvers that take risks and challenge cybersecuritys status quo. Its simple: we cant 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  .

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

Remote Work :

No

Employment Type :

Full-time