ML Engineer

What you'll do

• Design and scale ML pipelines for issue detection; train, evaluate, deploy, and monitor models.
• Improve anomaly detection and customer-specific models, including feedback and labeling loops.
• Work with customers and improve model speed, cost, and quality as event volumes grow.

What they ask for

• End-to-end ownership of ML systems, from data and training through deployment and monitoring.
• Track record of shipping production models that real users depend on.
• Experience scaling applications that serve millions of requests.
• Expertise in an area such as anomaly detection, classification, representation learning, or LLM fine-tuning.

Nice to have

• Use and build AI agents and tools.

AI focus

Develop and serve customer-specific models to detect unusual AI-agent behavior, including previously undefined issues; build feedback loops and bring detection methods into production.