Amazon Recruitment Drive; Hiring ML Data Associate II – Apply Now

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. Amazon 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. Their 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.

Name of the Organization: Amazon

Requisition ID: 280724002103

Positions: ML Data Associate II

Location: Chennai

No of Vacancy: 30

Salary: INR 3.5 - 4.5 LPA

Educational Qualifications:

• Bachelor's degree in a relevant field, such as Linguistics, Communications, or data-related disciplines.
• At least 6 months of experience with natural language data labeling, data annotation, linguistic annotation or other forms of data markup, and/or teaching experience.
• Experience identifying linguistic ambiguity and annotation inaccuracies in data.

Preferred qualifications:

• Familiarity with common text processing tools.
• Passion for language, linguistics, human language technology and AI.
• Knowledge of different domains such as Finance, Health Care, and Insurance.

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
• Collaborate with other ML Data stakeholders 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 ML Data linguists (MLDL), Language Engineers (LEs) and Team Managers (TMs) to innovate processes, tracker automations, and workflows.
• Assist LEs in communication with ML Data associates (MLDA) to provide detailed feedback to the annotators.

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