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    Data Generation Specialist - Boston, United States - Amazon

    Amazon background
    Paid Work
    Description

    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 generate data demonstrations to be used in Supervised Fine Tuning (SFT) of LLMs. The ideal candidate must demonstrate strong analytical and communication skills, attention to details, and a commitment to excellence.

    This is a nine month fixed temporary assignment

    Key job responsibilities

    As a Data Generation Specialist you will be responsible for generating data to train LLMs. The tasks will be complex in nature and will require the candidate to make informed and educated judgements in each case. The candidate will work closely with scientists and teams across the company to review provided guidelines, suggest updates to those guidelines, and engage in ongoing conversations regarding the quality of data. 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.

    Your key responsibilities will include (but not limited to) the below:


    • Work on complex processes and provide high quality data generations to customers.


    • Operate with autonomy


    • Leverage and demonstrate expertise in a wide array of areas, such as (but not limited to) Computer Science, Literature, Music, Mathematics, Economics and Travel


    • Perform audits and quality checks of tasks completed by other specialists, if required


    • Identify issues and proactively reports operational challenges


    • Contribute to root cause analysis and escalation management


    • Create, update and follow SOP/flow of processes


    • Identify process improvement opportunities (enhancements and pain points) at process/ function level


    • Demonstrate the ability to handle small to medium scale process improvement projects


    • Communicate to cross-company stakeholders on an ongoing basis to review a constantly evolving set of guidelines data and resolves emergent issues with minimal guidance


    • Contribute in mentoring / training junior data associates on an ongoing basis


    • Troubleshoot issues related to process and conduct root cause analysis if required

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

    Boston, MA, USA

    Basic Qualifications


    • Bachelor's Degree in a relevant field, such as Business Administration, Liberal Arts, Sciences, Computer Science, Engineering, Social Sciences, Visual and Performing Arts, or Communication.


    • Strong proficiency in English across verbal, written, reading, and comprehension skills.


    • Strong understanding of U.S.-based culture, society, and norms.


    • Strong interpersonal, analytical and communication skills.


    • Demonstrated passion for delivering a positive customer experience, and maintain composure in ambiguous and difficult situations.


    • Exceptional research skills to gather relevant information and understand complex topics.


    • Ability to adapt writing style to suit various style guidelines and customers.

    Preferred Qualifications


    • Working Knowledge of SQL, Python, and/or Machine Learning.


    • Familiarity with Large Language Models.


    • Experience in detailed content classification and data generation.


    • Experience working in ambiguous roles.

    Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit




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