ML Content Writer, AWS Bedrock

DESCRIPTION

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!

Amazon Web Services (AWS) is looking for a content writer to help with creating datasets for developing and testing the Bedrock models and services. As part of the Bedrock Data Team at AWS you will responsible for delivering high-quality training data to ensure the best performance of the AWS machine learning systems. Our goal is to produce the highest quality training data in the industry and to delight our customers by improving human language understanding and natural language processing.

The Bedrock team is a team of data associates and content writers 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

• Maintain and follow strict confidentiality as customer privacy is our biggest tenet
• Work with a range of different types of data including but not limited to text, speech, image, audio and video
• Maintain strict confidentiality and follow all applicable Amazon policies for securing confidential information
• Deliver high-quality labelled data, using guidelines provided to meet our KPIs, and using in-house tools and software
• Creative thinking and excellent written communication skills
• Work on testing for workflow launches if required
• Report issues with tools and software as and when they occur.
• Show Ownership and initiative when providing feedback for improvements to existing tooling that can increase the amount and quality of the data we process – we believe every ground-breaking change starts with a small idea!

About the team

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the 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.

BASIC QUALIFICATIONS

• Bachelor’s degree in a relevant field such as Journalism, Creative Writing, Linguistics.
• Experience identifying linguistic ambiguity and annotation inaccuracies in data.
• Ability to strictly adhere to annotation guidelines and identify basic parts of speech.

PREFERRED QUALIFICATIONS

• Master’s degree in a relevant field such as creative writing, journalism, linguistics etc.
• Passion for language, linguistics, human language technology and AI.
• Familiarity with json, yaml, xml or other forms of text markup.

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