Amazon is seeking an AI Editor with exceptional language skills who will bring innovation and creativity to our efforts to deliver a seamless and delightful AI-assisted shopping experience to customers worldwide. This is an opportunity to join the high-performing team behind Amazon’s generative AI-powered shopping assistant. Rufus makes it easy for customers to find and discover the best products to meet their unique needs by helping with product research, providing comparisons and recommendations, answering specific product questions, and more. This role is inherently high-visibility and highly cross-functional, requiring collaboration and influence across Amazon, including Editorial, Product, Science, Engineering, and Partner teams.
We are looking for candidates who are passionate about the intersection of language and technology and who are keen to develop automated, scalable solutions for training Large Language Models. This Editor will be responsible for using prompting and alignment data to improve the fluency of our Shopping AI model. They will uphold our high standards for style and tone, while using customer feedback to continually iterate and improve the shopping experience. Cross-functional partnership will be key, as this team works across the organization to evaluate CX metrics and drive continual model improvements.
This role requires exceptional written and oral communication skills, excellent judgment, strong interpersonal skills, deep curiosity about how things work, and a passion for serving customers. You must enjoy context-switching and partnering at all levels of the organization to deliver results. This is an opportunity to gain valuable experience in the growing field of artificial intelligence and its application in diverse business settings.
Key job responsibilities
* Translate complex content policies into prompts that LLMs can easily understand, ensuring alignment with business priorities
* Develop and utilize novel prompting approaches for feature development and defect reduction
* Create high-quality alignment data to train LLMs in shopping-specific use cases
* Identify potential biases or limitations in the LLMs responses and employ fine-tuning techniques to improve the model
* Become a subject matter expert across sensitive topics and policies, including areas ranging from environmental and medical claims to sexual content and profanity
A day in the life
You will develop and implement prompting strategies to train and improve Amazon’s Shopping LLM. You will partner closely with Product, Science, and Engineering teams, who are invested in creating solutions that make it easier, faster, and more intuitive for our non-coding workforce to iterate and improve Rufus for customers. You will be part of an Editorial team, which includes creative product and program managers, writers, editors, and language engineers. This is a startup culture: We move fast, have ambitious goals, adapt quickly, and learn along the way.
