Adversarial Machine Learning Engineer - Red Teaming
Tasks
- Analyze prompt injection
- Assess data poisoning risks
- Assess membership inference risks
- Assess model extraction risks
- Benchmark model security and safety
- Collaborate on remediation and validation
- Conduct adversarial testing
- Develop security evaluations for LLMs
- Evaluate model robustness
- Maintain threat models
- Perform red team assessments
- Produce vulnerability reports
- Retest implemented fixes
Perks/Benefits
Skills/Tech-stack
AI Risk Management Framework | Adversarial Machine Learning | Adversarial Robustness | Adversarial Robustness Toolbox | Adversarial Training | Adversarial examples | CleverHans | Data poisoning | Deep learning | Deployment Pipelines | Differential Privacy | Domain Adaptation | Experiment tracking | Fine Tuning | Foolbox | Hugging Face | Hugging Face Transformers | Input Sanitization | Instruction Tuning | LLM Applications | Linear Algebra | LoRA | MITRE ATLAS | MLOps | Machine Learning | Management Framework | Membership inference | Model extraction | Model versioning | NIST AI | NIST AI Risk | NIST AI Risk Management | NIST AI Risk Management Framework | OWASP Top | OWASP Top 10 | OWASP Top 10 for LLM | OWASP Top 10 for LLM Applications | Optimization | PEFT | Probability | PyTorch | Python | QLoRA | Risk Management Framework | Robust Fine Tuning | Secure deployment | Secure deployment pipelines | Statistics | TensorFlow | Threat modeling
Education
N/A
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