Tasks:
- * Build input validation and anomaly filtering pipelines
- * Detect sensor spoofing and data tampering
- * Develop automated model safety testing and evaluation tools
Perks/Benefits:
Skills/Tech stack required:
[Adversarial Robustness] [Adversarial Robustness Testing] [Automated testing] [CI/CD] [CNN] [Coverage analysis] [Data poisoning] [Docker] [FGSM] [Input validation] [Kubeflow] [Kubernetes] [MLflow] [MLOps] [Model Deployment] [PGD] [Python] [PyTorch] [Regression testing] [Robustness Testing] [TensorFlow] [Transformers] [Weights & Biases]
Educational requirements:
[Master's Degree]
Role(s):
[AI Safety Engineer] [Engineer] [Learning Engineer] [Machine Learning Engineer] [Safety Engineer]