AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI and the responsible development and deployment of large language models (LLMs) across all of our businesses.

We are looking for highly motivated and talented candidates who will review generated data demonstrations and provide human feedback to train LLMs. The ideal candidate must demonstrate strong analytical and communication skills, attention to details, and a commitment to excellence.


Key job responsibilities
• Work on clearly defined use cases, but leverage a high degree of judgement to produce preference data.
• Operate with autonomy
• Leverage and demonstrate expertise in a wide array of competencies such as (but not limited to) Computer Science, Literature, Music, Mathematics, Economics and Travel
• Identify issues and proactively report operational challenges
• Identify process improvement opportunities (enhancements and pain points) at process/ function level
• Demonstrate the ability to support small to medium scale process improvement projects
• Contribute in mentoring / training junior data associates on an ongoing basis
• Troubleshoot issues related to process and conduct root cause analysis if required


•Create original and engaging content across multiple work types to train LLMs.
•Write clear, concise, factually and grammatically correct responses that adheres to the Standard Operation Procedures (SOPs) and style guidelines to create visually appealing and effective content.
•Proofread and edit content to ensure high-quality standards, accuracy, and consistency.
•Research and verify content quality based on Content Guidelines. Approve or reject contents based on pre-defined guidelines and explain logical reasoning behind approve/reject decision.
•Perform quality checks by reviewing and proofreading; provide feedback and training to coworkers and cross-company teams to ensure that quality standards are met.
•Collaborate with cross-functional teams and other business units to monitor quality progress, investigate quality variations, develop and implement measures to drive quality improvement.
•Develop a deep understanding of the subject matter expert (SMEs) for processes on the floor and collaborate with stakeholder teams to test new SOPs to gather insights, validate information, and ensure accuracy in content creation.
•Support our leadership, business, and technical teams by actively participating in training, project/program management, etc., based on the group's needs and your own skills and inclinations.


A day in the life
As an AI Content Writer you will be responsible for reviewing machine and human generated demonstrations in order to generate preference data for training purposes. The tasks will be clearly defined, but will require a high degree of judgement in each case. The candidate will work closely with support teams, review guidelines, suggest updates to those guidelines, and engage in team calibrations to ensure the highest quality of data generation. You will also be a part of other initiatives across process improvements, SoP and guidelines formulation, diving deep to provide data insights as and when required.

BASIC QUALIFICATIONS

•Proven work experience as a Content Writer, Copywriter, or similar role.
•Strong proficiency in English. Candidate must demonstrate language proficiency in all the following: verbal, writing, reading and comprehension.

PREFERRED QUALIFICATIONS

•Prior experience of 2-4 years in content writing
•Bachelor’s or Master’s degree in a relevant field, such as Computer Science, Linguistics, Journalism, Communications, or a related area, with a strong emphasis on creative writing, technical writing, or AI technology to help train generative artificial intelligence models to become better writers.
•Ability to adapt writing style to suit various style guidelines and customers
•Ability to make logical decisions while performing tasks even when provided information is ambiguous
•Understanding of academic integrity, e.g: plagiarism