GO-AI QA Quality Specialist at Amazon

Worldwide

This is a full-time, permanent, remote position based in Costa Ricaand does not offer 7 relocation benefits. Job applicants must be located and legally authorized to work in Costa Rica in order to be eligible for consideration.<br/><br/>This is a non-technical operational role focused on delivering high-quality training data to improve and expand our Large Language Model (LLM) capabilities. The ML Data Associate II performs precise annotation tasks across multiple ML data process areas, drives process improvement, and provides day-to-day guidance to ML Data Associates I. Success in this role requires adherence to SOPs and sound human judgment—not programming skills. <br/><br/>Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of 21 race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.<br/><br/>Key job responsibilities<br/>- Perform precise, consistent annotations across multiple data types (image, video, and text), including object detection, semantic segmentation (pixel-level labeling), object tracking, and open-text evaluation. <br/>- Validate data against specific annotation guidelines, ensuring accuracy and high data integrity. <br/>- Write grammatically correct, creative, and technical texts in various styles, strictly adhering to complex project guidelines. <br/>- Apply strong judgment to address ambiguous situations or incomplete information; propose logical, consistent solutions when guidelines are insufficient. <br/>- Conduct audits and verifications of work completed by ML Data Associates I; document errors using standard tools and methods. <br/>- Resolve disputes for different programs within established SLA timelines. <br/>- Deliver structured coaching based on audit and dispute findings. <br/>- Identify error trends, perform root cause analysis within scope, and share findings with management. <br/>- Test new SOPs and tools; provide structured feedback on quality and recommend improvements. <br/>- Proactively identify day-to-day operational friction, bottlenecks, and tooling issues; formulate clear problem statements and communicate them to relevant stakeholders with manager review. <br/>- Contribute to the development and continuous improvement of audit methodologies, checklists, and test frameworks. <br/>- Participate in deep dives, research, global initiatives, process improvement efforts, new program launches, and UATs. <br/>- Provide day-to-day guidance to ML Data Associates I through training sessions and work reviews. <br/>- Conduct periodic refresher trainings to ensure SOP compliance across the team. <br/>- Support onboarding of new hires through content creation, delivery, and assessment. <br/>- Participate in and lead knowledge-sharing sessions related to new projects and guideline changes. <br/>- Achieve targeted productivity, quality, utilization, and other KPIs for executed tasks. <br/>- Collate, track, and report progress on key metrics to relevant stakeholders (Program Managers, - Applied Scientists, senior leaders). <br/>- Transition between 2–3 programs based on business needs and account requirements, adapting to varying use cases and schedules. <br/>- Quickly learn and efficiently utilize specialized annotation tools and platforms across evolving domains (e.g., packaging, manipulation, storage, sortation automation). <br/>- Support multiple projects simultaneously; accept re-prioritization as necessary. <br/>- Trained in more than one ML data labeling method and process; understands dependencies across ML data workflows and can articulate customer impact. <br/>- Experience in natural language data labeling, data annotation, linguistic annotation, or other forms of data markup. <br/>- Entry-level proficiency with MS Excel–based tools; ability to navigate and interpret data in spreadsheets. <br/>- Passion for process knowledge, accuracy, speed, and efficiency. <br/>- Strong collaboration skills; thrives in a fast-paced, dynamic work environment. <br/>- Demonstrates willingness to influence adoption of change within the team for established procedures and best practices. <br/>- Participates in hiring and enables ramp-up of new ML Data Associates. <br/><br/>About the team<br/>- Schedule available for this role is Monday-Friday 7:00am-4:00pm<br/>- Amazon is a multinational technology company with English as its core business language. Your recruiting/hiring team may be located in different jurisdictions, all CVs must be submitted in English to be eligible for consideration. Basic Qualifications: - Speak, write, and read fluently in English<br/>- 1+ years of customer service experience<br/>- High school diploma or equivalent Preferred Qualifications: - Experience in natural language data labeling, data annotation, linguistic annotation or other forms of data markup<br/><br/>Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit <a href="https://amazon.jobs/content/en/how-we-hire/accommodations">https://amazon.jobs/content/en/how-we-hire/accommodations</a> for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.