AI / ML Engineer

Responsibilities:

• Clean, label, and analyze SDK identity, device, and behavior data; build reproducible feature and training pipelines with time-based splits that prevent data leakage.
• Check label quality, missing signals, and consistency between training features and live inference inputs.
• Develop and compare baseline models for account takeover, bots, and scam indicators; combine model outputs and partner-engine signals into useful trust scores.
• Evaluate precision, recall, false positives, and performance across customer segments; document failure cases and develop clear reason codes for scores and decisions.
• Use confirmed fraud and false-positive feedback to improve datasets, monitor drift and retrain models, track experiments, and validate changes in shadow deployments.
• Collaborate with backend and SDK engineers on reliable, low-latency inference and partner-model integration; support liveness or deepfake evaluation where relevant as the roadmap develops.

Skills

AI, Accounts Takeover, Bots, Fraud, ML, Machine Learning, Python, Scam