Join Amazon's Artificial General Intelligence team and help shape the future of human-technology interaction. We are at the forefront of AI innovation, investing in generative AI and responsible LLM development. If you're driven to push boundaries and create impactful solutions, this is your opportunity to be part of something transformative.

As an ML Data Associate, you will be instrumental in foundational labeling tasks, including dialogue evaluation across speech, text, audio, and video data. Your role involves maintaining strict confidentiality, delivering high-quality labeled data according to guidelines, and utilizing in-house tools. You'll demonstrate proficiency in generating human insight data, making sound judgments with ambiguous information, and ensuring exceptional attention to detail. Your responsibilities extend to supporting daily operational deliverables, analyzing root causes of errors, proposing solutions for labeling quality, and identifying process improvements within Standard Operating Procedures. You will also provide floor support to clarify queries during execution.

To excel in this role, you need an Associate’s Degree or equivalent work experience, coupled with C1+ fluency in a specified language. Strong business writing skills are essential for creating reports and professional correspondence, alongside advanced reading comprehension for analyzing complex documents. You should possess well-developed analytical thinking and structured problem-solving capabilities, with a proven ability to interpret and implement detailed instructions across diverse projects. Proficient research skills for gathering and synthesizing information, meticulous attention to detail in managing complex tasks, and experience managing stakeholder relationships are crucial. Advanced proficiency in Microsoft Office Suite and common business applications is also required. A Bachelor’s degree in a relevant field and 2+ years of professional work experience are preferred, as is the ability to adapt to fast-paced, changing environments.