Senior Staff Machine Learning Engineer

What you'll do

• Design, build, and scale production ML systems for anomaly detection, threat detection, and security analytics.
• Manage the full ML lifecycle including feature engineering, training, deployment, monitoring, and retraining.
• Develop LLM and agentic AI capabilities for security investigations using retrieval-augmented generation (RAG).
• Create evaluation frameworks to measure model quality and ensure analyst trust in results.
• Build scalable data pipelines and resolve system bottlenecks in collaboration with data and platform engineers.
• Mentor other engineers and guide technical direction through design reviews and hands-on collaboration.

What we're looking for

• Experience running production ML systems from early experimentation through sustained operation at scale.
• Strong background training models with PyTorch and transformers, including behavioral modeling and anomaly detection.
• Proficiency with distributed compute like Spark, cloud platforms like AWS, and MLOps tools like MLflow.
• Experience building with LLMs or generative AI and evaluating their behavior in production.
• Strong Python and SQL skills combined with solid software engineering habits such as testing and code review.
• MS or PhD in computer science, machine learning, or a related field, or equivalent practical experience.
• Background applying ML to cybersecurity, fraud, or similar adversarial problems (preferred).
• Experience with vector databases, RAG, or multi-agent systems; publications, patents, or open-source contributions (preferred).