Machine Learning Engineer

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.

• 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

Corporate Overview

Proofpoint is a leading cybersecurity company protecting organizations’ greatest assets and biggest risks vulnerabilities in people. With an integrated suite of cloud-based solutions, Proofpoint helps companies around the world stop targeted threats, safeguard their data, and make their users more resilient against cyber-attacks. Leading organizations of all sizes, including more than half of the Fortune 1000, rely on Proofpoint for people-centric security and compliance solutions mitigating their most critical risks across email, the cloud, social media, and the web.

We are singularly devoted to helping our customers protect their greatest assets and biggest security risk their people. That’s why we’re a leader in next-generation cybersecurity.

Protection Starts with People. Proofpoint.

Location Sunnyvale, CA, USA, Hyderabad, A.P., India , Athens, Greece

Proofpoint is building the next generation of AI-powered security systems to protect organizations from rapidly evolving threats. We are looking for a highly skilled Machine Learning Engineer to help design and build production-grade ML systems that power intelligent security detections s role is focused on developing and deploying fine-tuned models that are small, fast, reliable, and cost-efficient — capable of operating in real-world, high-throughput security environments.

You will work closely with security researchers, platform engineers, and product teams to turn cutting-edge ML techniques into robust detection capabilities used in production. If you enjoy optimizing models for latency, efficiency, inference cost, and operational reliability — while solving difficult security problems — we’d love to talk to you.

• Design, train, fine-tune, and evaluate machine learning models for security detection use cases
• Build lightweight, high-performance models optimized for low latency, low inference cost, high throughput, operational reliability
• Develop fine-tuning pipelines for LLMs and smaller transformer-based models
• Experiment with techniques such as distillation, quantization, pruning, retrieval augmentation, parameter-efficient fine tuning (LoRA, adapters, etc.)
• Improve detection quality while minimizing false positives and false negatives
  - Build scalable ML infrastructure and production inference pipelines
• Partner with security researchers to transform detection logic into ML-powered systems
• Measure and optimize model performance across quality, speed, memory footprint, and cost
• Contribute to data engineering and labeling workflows for supervised training
  - Monitor production models and continuously improve robustness and reliability.

• Experience 2+ years of experience in Machine Learning Engineering or Applied AI
• Strong experience building and deploying ML systems in production
• Experience fine-tuning transformer models or LLMs Strong Python engineering skills
• Experience with modern ML…