ML Engineer (Fraud Detection)

TL;DR

ML Engineer (Fraud Detection): Developing and optimizing multimodal integrity systems to detect assessment fraud with an accent on adversarial ML and signal fusion. Focus on building evaluation infrastructure and designing high-precision models that adapt to evolving attack surfaces.

Location: Hybrid in Santa Clara, CA

Company

hirify.global is a platform that helps companies identify and invest in next-generation technical talent based on skills rather than pedigree.

What you will do

• Standardize model quality measurement and build evaluation infrastructure, golden datasets, and benchmarking pipelines.
• Own performance improvement strategies for integrity signals by exploring new architectures and training paradigms.
• Define ML strategies from scratch for new signal categories including audio analysis, gaze tracking, and behavioral anomalies.
• Monitor the evolution of assessment fraud tooling and evaluate emerging models to maintain a competitive edge.
• Systematically address edge cases and convert customer-reported failures into improved model robustness.
• Drive strategy-level decisions on which new signals to build and the evidence required for production readiness.

Requirements

• Proven experience shipping ML systems in production used by real businesses.
• Deep intuition for identifying and fixing precision leaks systematically.
• Strong systems thinking, integrating data pipelines, serving infrastructure, and business outcomes.
• Expertise in evaluation methodology and metric precision.
• Must be based in or able to work hybrid in Santa Clara, CA.

Nice to have

• Experience with production multimodal systems (vision, audio, or behavioral signal pipelines).
• Background in adversarial ML or fraud/anomaly detection.
• Publications or open-source contributions in detection, robustness, or model evaluation.
• Experience defining production-ready standards for new signal categories.

Culture & Benefits

• High-standards environment focused on impact and attention to detail.
• Opportunity to work on complex, adversarial problems where the threat landscape constantly shifts.
• Work with a product trusted by over 2,500 innovative companies worldwide.
• Equal opportunity and affirmative action employer.