Description

　　Alexa Shopping Operations strives to become the most reliable source for dataset generation and annotations. We work in collaboration with Shopping feature teams to enhance customer experience (CX) quality across shopping features, devices, and locales. Our primary focus lies in handling annotations for training, measuring, and improving Artificial Intelligence (AI) and Large Language Models (LLMs), enabling Amazon to deliver a superior shopping experience to customers worldwide. Our mission is to empower Amazon's LLMs through Reinforcement Learning from Human Feedback (RLHF) across various categories at high speed. We aspire to provide an end-to-end data solution for the LLM lifecycle, leveraging cutting-edge technology alongside our operational excellence. By joining us, you will play a pivotal role in shaping the future of the shopping experience for customers worldwide.

　　Key job responsibilities

　　As part of your role, you will have the opportunity to:

　　• Process annotation & data analysis tasks with high efficiency and quality in a fast paced environment

　　• Provide floor support to Operations manager in running day to day operations working closely with Data Associates

　　• Handle work prioritization and deliver based on business needs

　　• Track and report ops metrics and ensure delivery on all KPIs and SLAs

　　• You will work closely with your team members and managers to drive process efficiencies and explore opportunities for automation

　　• You will strive to enhance the productivity and effectiveness of the data generation and annotation processes

　　• The tasks will be primarily repetitive in nature and will require the individual to make judgment-based decisions keeping in mind the guidelines provided in the SOP.

　　We are open to hiring candidates to work out of one of the following locations:

　　Bucharest, RO

　　About the team

　　Alexa Shopping Operations strives to become the most reliable source for dataset generation and annotations. We work in collaboration with Shopping feature teams to enhance customer experience (CX) quality across shopping features, devices, and locales. Our primary focus lies in handling annotations for training, measuring, and improving Artificial Intelligence (AI) and Large Language Models (LLMs), enabling Amazon to deliver a superior shopping experience to customers worldwide. Our mission is to empower Amazon's LLMs through Reinforcement Learning from Human Feedback (RLHF) across various categories at high speed. We aspire to provide an end-to-end data solution for the LLM lifecycle, leveraging cutting-edge technology alongside our operational excellence. By joining us, you will play a pivotal role in shaping the future of the shopping experience for customers worldwide

　　We are open to hiring candidates to work out of one of the following locations:

　　Bucharest, ROU

　　Basic Qualifications

　　• Proficiency in both English and German (C1/C2 Level)

　　• Experience in content or editorial writing

　　Preferred Qualifications

　　Bachelor's degree in Science, Computer Science or German stream, or equivalent

　　Outstanding communication skills, both written and oral, with a keen eye for detail

　　Strong organizational skills to effectively manage tasks and projects

　　Proficient in analytical thinking and problem-solving

　　Comfortable working in a fast-paced, highly collaborative, and dynamic work environment

　　German language certificates: DSD II, DaF

　　Previous experience as AI trainers, knowledge of AI and NLP, Cambridge certifications

　　Experience with Artificial Intelligence interaction, such as prompt generation and open AI's

　　Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.