Member of Technical Staff

Wwshemi; New York (NY); On-site; USD 120,000 - 170,000; Full time

Job summary

Wwshemi in New York is seeking a role focused on building and deploying detection models and the surrounding systems to support fraud detection, identity, and trust & safety initiatives.

You will collaborate with cross-functional teams to turn evidence into actionable decisions and workflows, while developing robust methods that remain effective against evolving adversaries.

Qualifications

• Experience in CV/image forensics, speech or video analysis, ML infra, evaluation or calibration, or trust & safety systems.
• Experience owning end-to-end problems and shipping detection models or related interfaces.
• Experience evaluating model performance and identifying failure modes amid evolving threats.
• Experience collaborating with trust/fraud teams to translate evidence into decisions and workflows.

Responsibilities

• Build and ship detection models and the systems around them.
• Measure system performance, identify failure modes, and iterate as conditions change.
• Work directly with trust and fraud teams to turn evidence into decisions and usable workflows.
• Develop approaches that stay effective as adversaries adapt.

Skills

Computer Vision

ML infrastructure

Fraud systems

Trust & Safety

Job description

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Own technical problems end to end, from analyzing forensic signals to building models and product systems used by fraud analysts. This work supports fraud detection, identity, and trust-and-safety efforts against evolving adversarial threats.

What You'll Do

• Build and ship detection models and the systems around them.
• Measure system performance honestly, identify failure modes, and iterate as conditions change.
• Work directly with trust and fraud teams to turn evidence into decisions and usable workflows.
• Develop approaches that remain effective as adversaries adapt.

What We're Looking For

• Technical experience in at least one relevant area: computer vision or image forensics, speech or audio modeling, video or temporal analysis, ML infrastructure, evaluation or calibration, fraud, identity or trust and safety systems, or full-stack product engineering.
• Experience owning technical problems end to end and shipping detection models, supporting systems, or product experiences.
• Experience evaluating model or system performance, identifying failure modes, and improving solutions in response to changing threats.
• Experience working with trust and fraud teams to translate evidence into decisions and product workflows.

Location

Primary location: New York, United States. The work arrangement was not specified.