Palo Alto Networks · 1 day ago
Principal Engineer Machine Learning (MLOps DLP Detection)
Santa Clara, CA
Full-time
Onsite
Lead/Staff
$175K/yr - $220K/yr
8+ years expPalo Alto Networks is a cybersecurity company committed to protecting the digital way of life. They are seeking a Principal MLOps Engineer to lead the design and operation of machine learning infrastructure, ensuring the reliability and governance of AI/ML systems.
Agentic AICloud SecurityCyber SecurityNetwork SecuritySecurity
Responsibilities
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
Qualification
Required
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+ years 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
Benefits
Restricted stock units
Bonus
Company
Palo Alto Networks
Palo Alto Networks is a cybersecurity company that offers cybersecurity solutions for organizations.
10001+ employees
H1B Sponsorship
Palo Alto Networks has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (579)
2024 (482)
2023 (341)
2022 (452)
2021 (493)
2020 (235)
Funding
Current Stage
Public CompanyTotal Funding
$65MKey Investors
Icon VenturesLehman HoldingsGlobespan Capital Partners
2012-07-20IPO
2008-11-03Series C· $10M
2008-08-18Series C· $27M
Leadership Team
Helmut Reisinger
CEO EMEA
Nikesh Arora
Chairman CEO
Recent News
2026-01-09
2026-01-08
Company data provided by crunchbase