ML Engineer

Raindrop • San Francisco, CA

19h

About The Position

Raindrop is seeking an ML Engineer to improve the accuracy, speed, and cost of its issue-detection system. The role owns models that detect anomalies across hundreds of millions of AI-agent events, from training through production. The engineer will develop and operate small, private models tailored to individual customers, improve models using customer signals, and help scale detection as event volume grows. As part of an early team, the engineer will contribute to product and company decisions, work directly with customers, and bring new detection methods into production.

Requirements

• Ownership of ML systems end to end, from data and training through deployment and monitoring.
• A track record of shipping models to production 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.
• Good judgment about when to move fast and when to build for the long term.
• Use and build AI agents and tools.

Responsibilities

• Design, build, and scale the ML pipelines behind Raindrop’s issue detection.
• Train, evaluate, and deploy models, and monitor their quality in production.
• Iterate quickly without sacrificing quality.
• Work with customers to understand how their agents fail and what they need to catch.
• Bring new detection methods into production.
• Improve anomaly detection across customer production data, including issues that have not been defined in advance.
• Train and serve small, private models for each customer and improve their accuracy over time.
• Build feedback loops that turn customer signals into better models.
• Keep models fast and affordable as event volume grows.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed