Senior Fraud ML Engineer: Production-Ready Models

Jobtailor; California (MO); On-site; USD 120,000 - 170,000; Full time

Job summary

Jobtailor is seeking an experienced ML Engineer to advance fraud detection systems. You will design and deploy models, build robust training pipelines, and collaborate with Data Science, Product, and Engineering teams to scale solutions across customers.

Responsibilities include feature engineering, model evaluation, and exploring transformer-based approaches to improve production performance, with emphasis on reducing false positives and maintaining throughput.

Qualifications

• Strong ML fundamentals and feature engineering.
• Experience designing, training, tuning, deploying models.
• Experience with evaluating production performance.
• Hands-on Python programming.
• SQL proficiency for data handling.
• Experience with PyTorch / scikit-learn / XGBoost.
• Fraud or risk modeling experience preferred.

Responsibilities

• Investigate fraud patterns and model errors to identify signals and improve detection.
• Develop training datasets and predictive features addressing label quality and imbalance.
• Design, train, and tune models using gradient-boosted trees and neural networks.
• Evaluate newer model architectures against existing approaches.
• Lead ML projects from experiments through model release with teams.
• Deploy models with engineering and ML infrastructure partners.
• Explore LLMs and Generative AI for fraud detection and investigation.

Job description

Jobtailor is seeking an experienced ML Engineer to advance fraud detection systems. You will design and deploy models, build robust training pipelines, and collaborate with Data Science, Product, and Engineering teams to scale solutions across customers.

Responsibilities include feature engineering, model evaluation, and exploring transformer-based approaches to improve production performance, with emphasis on reducing false positives and maintaining throughput.