Amazon Web Services (AWS) is looking for a data associate to help with annotations and data analysis. As part of the Ai 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.

Key job responsibilities
* Build a thorough understanding of data collection and annotation guidelines and various annotation tools.
* Annotate, generate and QA data, identifying linguistic categories based on detailed annotation and adhering to guidelines.
* Use generative AI to facilitate workflows or automate repetitive tasks
* Monitor AI outputs for biases or ethical issues and adjusting inputs to mitigate these risks.
* Perform annotation related tasks; you participate in data generation, collection and quality assurance tasks
* Collaborate with other ML Data Linguists to resolve data ambiguities and annotation disagreements.
* Dive deep into the data to perform qualitative error trend analysis, and devise action plan to improve data quality.
* Provide feedback to Language Engineers and Scientists on tool improvements and annotation processes.
* Diving deep into issues and implement solutions independently
* Contribute to process improvements to reduce handling time and improve resource output.
* Develop a variety of language artifacts crucial for model development such as datasets for training and evaluation.
* Support and consult in pre-screening interviews for Data Associates.
* Collaborate with LEs, scientists, and Ops Manager to innovate processes, tracker automations, and workflows.
* Assist LEs in communication with vendor to provide detailed feedback to annotators.

About the team
The Bedrock team is a team of data linguists who primarily support the training of different models in the AWS generative AI platform. We work with different model types, such as text-to-text, text-to-image, text-to-speech, and others, generating data for ML model training, as well as toxic content evaluation, and categorization. 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.