Anthropic's AI technology is amongst the most capable and safe in the world. However, large language models are a new type of intelligence, and the art of instructing them in a way that delivers the best results is still in its infancy - it's a hybrid between programming, instructing, and teaching. We're bringing rigor to this new discipline by applying a range of techniques to systematically discover and document prompting best practices, and finding ways of making it easy for our customers to do the same. Given that the field of prompt-engineering is arguably less than 2 years old, this position is a bit hard to hire for. As a result, we ask that you share with us a specific prompt engineering project on LLMs that you're proud of in your application. Ideally this project should show off a complex and clever prompting architecture or a systematic evaluation of an LLM's behavior. If you have extensive ML experience, we'd take a complex ML project that involved careful dataset curation and processing as well as extensive benchmarking as a substitute. Responsibilities:
- Manage and mentor prompt engineers, providing both technical guidance and career development.
- Set goals and reviews for your team, promoting growth and output.
- Stay on top of latest advancements in ML and prompt engineering and adjust team direction accordingly.
- Help set team best practices for how prompting research and development is done, including introducing rigorous procedures for benchmarking and optimizing prompt performance.
- Manage the creation of a library of high quality prompts or prompt chains to accomplish a variety of tasks, with an easy guide to help users search for the one that meets their needs.
- Work with a handful of highest-value enterprise customers on their prompting strategies.
You may be a good fit if you:
- Have experience managing high performance teams of engineers or scientists
- Have an organizational mindset and enjoy building teams from the ground up.
- Have excellent communication, collaboration, and coaching abilities.
- Are comfortable dealing with highly uncertain, ambiguous, and fast-moving environments.
- Have a creative hacker spirit and love solving puzzles.
- Have at least a high level familiarity with the architecture and operation of large language models as well as ML in general.
- Have a firm grasp of programming in Python and experience with data structures/algorithms.
- Think holistically and can proactively identify the needs of an organization.
- Make ambiguous problems clear and identify core principles that can translate across scenarios.
- Have a passion for making powerful technology safe and societally beneficial.
- Think creatively about the risks and benefits of new technologies, and think beyond past checklists and playbooks.
- Stay up-to-date and informed by taking an active interest in emerging research and industry trends.
Deadline to apply:None. Applications will be reviewed on a rolling basis.