We're looking for a meticulous professional to spearhead our efforts in large language model quality assurance.
* Conduct adversarial testing of AI/LLM outputs to identify potential security risks.
* Evaluate AI prompts across various domains, such as finance and healthcare, to assess their effectiveness and safety.
* Develop test cases to evaluate accuracy, bias, and toxicity in AI-generated content.
In this role, you'll work closely with data scientists and safety researchers to identify and mitigate potential risks associated with AI systems. Your key responsibilities will include:
* Red Teaming Exercises: Conduct in-depth analyses of AI/LLM outputs to identify vulnerabilities and potential security threats.
* Prompt Evaluation: Assess the effectiveness and safety of AI prompts across various domains, including finance, healthcare, and security.
* Quality Assurance: Develop and implement test cases to evaluate the accuracy, bias, and toxicity of AI-generated content.
To succeed in this role, you'll need to possess a strong background in Quality Assurance, content review, or test case development for AI/ML systems. Additionally, experience in AI red teaming, LLM safety testing, or adversarial prompt design is highly desirable. You should have excellent critical thinking, pattern recognition, and analytical writing skills, as well as the ability to work independently and meet tight deadlines. If you're passionate about ensuring the safety and efficacy of AI systems, we encourage you to apply for this exciting opportunity.
We offer a unique chance to contribute to the development of AI/ML systems that benefit society while minimizing potential risks. As a member of our team, you'll have the opportunity to collaborate with industry experts and thought leaders in the field of AI safety.