About Us:

Proofpoint is a global leader in human- and agent-centric cybersecurity. We protect how people, data, and AI agents connect across email, cloud, and collaboration tools. Over 80 of the Fortune 100, 10,000 large enterprises, and millions of smaller organizations trust Proofpoint to stop threats, prevent data loss, and build resilience across their people and AI workflows. Our mission is simple: safeguard the digital world and empower people to work securely and confidently. Join us in our pursuit to defend data and protect people.

How We Work:

At Proofpoint you’ll be part of a global team that breaks barriers to redefine cybersecurity guided by our BRAVE core values:

Bold in how we dream and innovate

Responsive to feedback, challenges and opportunities

Accountable for results and best in class outcomes

Visionary in future focused problem-solving

Exceptional in execution and impact

The Role

We are seeking a Senior MLOps Engineer to join our Machine Learning and Data Science Team at Proofpoint. This role is key to building and maintaining the infrastructure that brings machine learning models from development to production. Your contributions will directly impact how fast and safely we ship ML models to production, reinforcing Proofpoint's mission to protect organizations from security risks.

What you'll do:

• Design, build, and maintain CI/CD pipelines for ML model training and deployment (Harness, GitHub Actions, or similar).
• Manage container images, base image governance, and vulnerability remediation for ML inference services.
• Deploy and operate ML inference endpoints on Kubernetes across AWS and Azure environments to ensure our inference services are secure, scalable and reliable.
• Lead FedRAMP compliance efforts for ML infrastructure: security controls, audit preparation, vulnerability scanning (Snyk, CIS), and remediation.
• Manage cloud resources (GPU nodes, compute clusters, IRSA configurations) to support model serving at scale.
• Collaborate with data scientists and ML engineers to streamline the path from experiment to production.
• Monitor infrastructure health, model serving performance, and cost efficiency across clusters.
• Maintain documentation for deployment processes, security reviews, and infrastructure architecture.
• Stay current with MLOps tooling, cloud-native technologies, and security best practices.

What we're looking for:

• 5+ years of machine learning experience with frameworks like (PyTorch, TensorFlow); model serving is a plus.
• Strong Proficiency in Python, with experience in infrastructure-as-code tools (Terraform, Helm, or similar).
• Strong experience with Kubernetes (deployment, scaling, troubleshooting) in production environments.
• Hands-on experience with CI/CD platforms (Harness, Jenkins, GitHub Actions).
• Familiarity with container security: image scanning, vulnerability management, base image pipelines.
• Experience with AWS services (S3, SageMaker, EKS, ECR, IAM/IRSA) and Azure (AKS, Azure ML).
• Knowledge of security compliance frameworks (FedRAMP Moderate, SOC2, or similar).
• Experience with ML model serving frameworks (TorchServe, Triton, or custom inference endpoints).
• Strong SQL skills for querying operational and telemetry data.
• Familiarity with observability tools (Prometheus, Grafana, Datadog) for monitoring ML systems.

Why Proofpoint?

At Proofpoint, we believe that an exceptional career experience includes a comprehensive compensation and benefits package. Here are just a few reasons you’ll love working with us:

• Competitive compensation

• Comprehensive benefits

• Career success on your terms

• Flexible work environment

• Annual wellness and community outreach days

• Always on recognition for your contributions

• Global collaboration and networking opportunities

Our Culture:

Our culture is rooted in values that inspire belonging, empower purpose and drive success-every day, for everyone.

We encourage applications from individuals of all backgrounds, experiences, and perspectives. If you need accommodation during the application or interview process, please reach out to [email protected].

How to Apply

Interested? Submit your application along with any supporting information- we can’t wait to hear from you!