Machine Learning Engineer, Integrity
Tasks
- Build evaluation infrastructure for integrity signals
- Create golden datasets and benchmarking pipelines
- Define ML strategy for new signals
- Detect strategy drift and abandon ineffective approaches
- Drive decisions on new signals and model usage
- Explore new architectures and training paradigms
- Improve performance for each signal
- Monitor assessment fraud tooling and evaluate new models
- Set production ready data and architecture requirements
- Surface edge cases and create training data
- Turn customer failures into harder to fool models
Perks/Benefits
- N/A
Skills/Tech-stack
Adversarial Machine Learning | Anomaly Detection | Audio analysis | Behavioral analytics | Benchmarking | Classification | Computer Vision | Data Pipelines | Drift Detection | Fraud Detection | Inference Systems | Machine Learning | Model Evaluation | Monitoring | Multimodal Learning | Multimodal fusion | Uncertainty Estimation
Education
N/A
Regions
Countries
States
Cities
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