Ml Data Associate I, Aws Bedrock

Bachelor's degree
- Speak, write, and read fluently in English

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.
Are you someone who cares about customer experience, do you have a passion for Operations Management and Machine Learning? If so, then we're looking for you
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
Attention to detail (linguistically and culturally)
Strong grammar skills
Critical thinking and analytical skills when it comes to evaluating linguistic data (ask questions)
Ability to identify potential biases (and be aware of your own biases)
Sufficient annotator experience to identify when there is a major issue with the task that should be escalated
Experience in some specific domains, like healthcare, finance, retail, etc
Having strong writing/communication skills to communicate with stakeholders.
Quality assurance experience
Good research and reading comprehension skills.
Willing to work round in PST timezone.
A day in the life
We are looking for a Data Associate (DA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech & text data, to assess and improve performance in everyday situations.
To make a mark, one needs to be an expert, your adaptability, focus, and attention to detail in a dynamic need to be unparalleled. To pride yourself on your ability to recognize issues, not succumb to pressure, but come up with an elegant and innovative solution to tackle any hurdle from the goal while working on multi-data modalities.
About the team
Diverse Experiences
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.
- Bachelor's degree in a relevant field, such as Linguistics, Communications, a foreign language, or other language or data-related disciplines, including teaching.
- Experience with natural language data labeling, data annotation, linguistic annotation or other forms of data markup.