AI Safety Systems Engineer vs AI SDK Engineer

A AI Safety Systems Engineer Only

• Machine learning fundamentals including transformer architectures, fine-tuning, and inference pipelines
• AI alignment techniques such as RLHF, Constitutional AI, and reward modeling
• Red teaming and adversarial testing of language models and multimodal systems
• Prompt injection detection, jailbreak prevention, and input/output sanitization
• Building and deploying content moderation and toxicity classification pipelines
• LLM observability, tracing, and runtime monitoring using specialized platforms
• Threat modeling for AI systems covering data poisoning, model extraction, and misuse vectors
• Python software engineering with emphasis on testing frameworks and CI/CD for ML