Machine Learning Engineer, Detection (NY)

Doppel is building an AI-native social engineering defense platform that monitors billions of domains and digital assets to identify and neutralize threats at scale. We're seeking a Machine Learning Engineer to design, train, and deploy detection models that protect enterprises from phishing, impersonation, and fraud across digital channels.

About the Role

As a Machine Learning Engineer on the Detection team, you'll build and scale the models and systems powering Doppel's threat identification across diverse data sources. You'll work on both batch and real-time inference systems handling high-throughput data ingestion, collaborating with Detection and Infrastructure teams to ensure production reliability and performance at enterprise scale.

Responsibilities

• Design, train, and deploy machine learning models for batch and real-time inference that identify malicious or infringing content across multiple data sources
• Partner with Detection and Infrastructure teams to optimize ML systems for high-volume web data processing and scaling
• Develop solutions spanning NLP, embeddings, similarity search, classification, and anomaly detection for threat detection workflows
• Work directly with customers and internal stakeholders to translate real-world threats and adversarial patterns into production ML systems

Requirements

• Proven experience building and deploying machine learning systems in production environments
• Proficiency working with large-scale datasets and distributed data processing frameworks
• Strong understanding of trade-offs between research-quality models and production-ready systems
• Ability to tackle evolving adversarial problems where threat landscapes change continuously

Benefits

• Free lunch and dinner in office
• Flexible PTO
• Quarterly team offsites
• Mission-driven culture with low ego and high ownership

Location: New York