About the role
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 We are seeking a Machine Learning Engineer with at least 3-4 years of software engineering and ML systems experience to join our collaborative Machine Learning Engineering Team at Proofpoint. This role is integral to designing, building, and scaling production ML systems for cybersecurity challenges. You will take ownership of the full ML lifecycle—from data pipelines and feature engineering to model training, serving, and monitoring at scale. You will work closely with data scientists, data engineers, and security teams to build robust, performant systems that detect and prevent cyber threats in real time. What You Bring to
the Team As a core team member, you will play a crucial role in architecting scalable ML systems and ensuring production excellence. You will own the end-to-end development and deployment of ML models, from infrastructure design to optimization and monitoring. You work closely with data scientists, MLOps engineers, data engineers, and security specialists to ensure models scale, perform reliably, and integrate seamlessly into our production environments. We are looking for someone with a strong software engineering foundation—solid CS fundamentals, system design experience, and a proven track record building production systems. You should have hands-on experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn) and the engineering discipline to write clean, testable, maintainable code. Experience with ML deployment platforms, model serving, feature stores, and monitoring systems is essential. Familiarity with adversarial ML, cybersecurity challenges, and NLP is a plus, but we prioritize strong engineering fundamentals and the ability to learn new ML domains quickly. Your contributions will drive our ability to build reliable, scalable systems that detect cyber threats at scale, reinforcing Proofpoint's mission to protect organizations from security risks. Day-to-Day
