Staff ML Engineer — Real-Time Fraud Detection

AppGate; New York (NY); On-site; USD 180,000 - 220,000; Full time

Job summary

A leading technology firm is seeking a Staff Machine Learning Engineer to lead the design of an AI-driven fraud detection platform. This role involves architecting scalable ML systems, developing end-to-end ML pipelines, and collaborating with cross-functional teams. The ideal candidate has over 5 years of experience in ML and fraud detection, expertise in Python, and knowledge of big data systems. Competitive compensation ranging from $180,000 to $220,000 plus a bonus is offered.

Qualifications

• 5+ years experience building ML or AI systems in production; at least 2 in fraud, risk, or anomaly detection.
• Proven track record designing and maintaining ML pipelines at scale.
• Strong understanding of supervised/unsupervised learning and statistical modeling.

Responsibilities

• Architect and build scalable ML systems for fraud detection.
• Develop and maintain end-to-end ML pipelines.
• Leverage modern AI techniques for fraud detection improvements.

Skills

Python

Machine Learning frameworks (PyTorch, TensorFlow, scikit-learn)

CI/CD (GitHub Actions, Jenkins)

Data collaboration and communication

Big data and distributed systems (Spark, Kafka, Flink)

Tools

AWS

GCP

Azure

Docker

Kubernetes

Job description

A leading technology firm is seeking a Staff Machine Learning Engineer to lead the design of an AI-driven fraud detection platform. This role involves architecting scalable ML systems, developing end-to-end ML pipelines, and collaborating with cross-functional teams. The ideal candidate has over 5 years of experience in ML and fraud detection, expertise in Python, and knowledge of big data systems. Competitive compensation ranging from $180,000 to $220,000 plus a bonus is offered.