Software Engineer, Trust & Safety
Anthropic Limited - San Francisco, CA
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Scroll down to find an indepth overview of this job, and what is expected of candidates Make an application by clicking on the Apply button.About the role:We are looking for software engineers to help build safety and oversight mechanisms for our AI systems. As a trust and safety software engineer, you will work to monitor models, prevent misuse, and ensure user well-being. This role will focus on building systems to detect unwanted model behaviors and prevent disallowed use of models. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies.Responsibilities:Develop monitoring systems to detect unwanted behaviors from our API partners and potentially take automated enforcement actions; surface these in internal dashboards to analysts for manual reviewBuild abuse detection mechanisms and infrastructureSurface abuse patterns to our research teams to harden models at the training stageBuild robust and reliable multi-layered defenses for real-time improvement of safety mechanisms that work at scaleAnalyze user reports of inappropriate content or accountsYou may be a good fit if you:Bachelor's degree in Computer Science, Software Engineering or comparable experience3-10+ years of experience in a software engineering position, preferably with a focus on integrity, spam, fraud, or abuse detection.Proficiency in SQL, Python, and data analysis tools.Strong communication skills and ability to explain complex technical concepts to non-technical stakeholdersStrong candidates may also:Have experience building trust and safety mechanisms for AI/ML systems, such as fraud detection models or security monitoring tools or the infrastructure to support these systems at scaleHave experience with machine learning frameworks like Scikit-Learn, Tensorflow, or Pytorch, and experience building machine learning modelsHave experience with prompt engineering, jailbreak attacks, and other adversarial inputsHave worked closely with operational teams to build custom internal toolingDeadline to apply:None. Applications will be reviewed on a rolling basis.#J-18808-Ljbffr
Created: 2025-01-01