Security ML Engineer — Real-Time Threat Detection

Proofpoint; Sunnyvale (CA); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive compensation

Comprehensive benefits

Flexible work environment

Job summary

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 design and build production-grade ML systems that power intelligent detections at scale.

This role focuses 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.

Qualifications

• 2+ years in Machine Learning Engineering or Applied AI.
• Experience deploying ML systems in production.
• Strong Python and ML framework skills (PyTorch/Hugging Face; TensorFlow optional).

Responsibilities

• Design, train, fine-tune ML models for security detection use cases.
• Build lightweight, high-performance models optimized for low latency and cost.
• Develop fine-tuning pipelines for LLMs and smaller transformer-based models.
• Collaborate with security researchers to transform detection logic into ML-powered systems.
• Measure and optimize model performance across quality, speed, memory footprint, and cost.

Skills

Python

ML Engineering

Production ML

PyTorch

Hugging Face

TensorFlow

Cloud deployment

Data pipelines

Distributed training

Tools

PyTorch

Hugging Face

TensorFlow

Job description

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 design and build production-grade ML systems that power intelligent detections at scale.

This role focuses 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.