ML Data Associate I, AWS Bedrock at Amazon
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reinforcement learning
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AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.
The Bedrock team is a team of data linguists and associates who primarily support the training of different models in the AWS generative AI platform. We are specialized in text-based data annotation, writing for ML model training, and toxic content evaluation. Some of the aspects of ML development that the Bedrock team works with include Responsible AI, Reinforcement Learning from Human Feedback, Supervised Fine Tuning, and Human Content Evaluation. Our team represents a great array of experience in the field of linguistics, including sociolinguistics, computational linguistics, conversation analysis, syntax-semantics, linguistic typology, ESL and foreign languages, as well as translation.
Key job responsibilities
* Build a thorough understanding of data collection and annotation guidelines and various annotation tools.
* Annotate text data, identifying linguistic categories based on detailed annotation and adhering to guidelines.
* Perform annotation related tasks; you participate in data generation, collection and quality assurance tasks
* Diving deep into issues and implement solutions independently
* Collaborate with ML Data Associates (L3) and Team Managers (TMs) to deliver high quality data annotations
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
The Bedrock team is a team of data linguists and associates who primarily support the training of different models in the AWS generative AI platform. We are specialized in text-based data annotation, writing for ML model training, and toxic content evaluation. Some of the aspects of ML development that the Bedrock team works with include Responsible AI, Reinforcement Learning from Human Feedback, Supervised Fine Tuning, and Human Content Evaluation. Our team represents a great array of experience in the field of linguistics, including sociolinguistics, computational linguistics, conversation analysis, syntax-semantics, linguistic typology, ESL and foreign languages, as well as translation.
Key job responsibilities
* Build a thorough understanding of data collection and annotation guidelines and various annotation tools.
* Annotate text data, identifying linguistic categories based on detailed annotation and adhering to guidelines.
* Perform annotation related tasks; you participate in data generation, collection and quality assurance tasks
* Diving deep into issues and implement solutions independently
* Collaborate with ML Data Associates (L3) and Team Managers (TMs) to deliver high quality data annotations
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.