Senior ML Engineer – Fraud & Bot Detection

Castle (Headquarters: )

ML Machine Learning AI Fraud Detection Bot Detection Anomaly Detection Adversarial ML LLM Behavioral Clustering Vector Search Real-time Python Security Fintech Remote EMEA Behavioral Intelligence Fingerprinting AI Engineer Data Science Staff Engineer

Castle is a YC-backed Series A startup building modern, AI-powered bot detection and abuse prevention technology used by companies like Canva, Atlassian, and Rockstar Games. We focus on real-time protection and behavioral intelligence to fight fraud and abuse. We are a small, fast-moving team committed to staying ahead of attackers.

As a Senior ML Engineer, you'll join our research team to combat bots and malicious actors using cutting-edge techniques. You will be instrumental in developing and deploying the machine learning models at the heart of our detection capabilities.

Responsibilities:
- Design, build, and maintain real-time ML pipelines for fraud and bot detection.
- Develop and implement anomaly detection algorithms to identify suspicious behavior.
- Research and apply adversarial ML techniques to counter evolving threats.
- Combine traditional fraud signals with modern AI approaches, including LLMs, behavioral clustering, and vector-based search.
- Own the end-to-end lifecycle of ML models, from research and development to deployment and monitoring in production.
- Deploy models rapidly and iterate based on performance metrics and feedback.
- Work directly with Castle's rich, structured behavioral data and highly accurate device fingerprinting intelligence (99.5% accurate).
- Collaborate with the engineering team to integrate models into our platform, which includes behavioral analysis tools, AI scoring, rules engines, and case management systems.

Ideal Candidate:
- Strong industry experience in the anti-fraud and/or anti-bot detection field is essential.
- Proven track record of building and deploying machine learning models in production, particularly for real-time applications.
- Deep understanding of ML concepts relevant to anomaly detection and adversarial scenarios.
- Experience with modern AI techniques (LLMs, vector databases, clustering) is highly desirable.
- Proficient in relevant programming languages (e.g., Python) and ML frameworks.
- Passionate about applying cutting-edge ML to solve real-world security problems and making an immediate impact.
- Thrives in a fast-paced startup environment.