Alexa is the voice activated digital assistant powering devices like Amazon Echo, Echo Dot, Echo Show, and Fire TV, which are at the forefront of this latest technology wave. To preserve our customers’ experience and trust, the Alexa Sensitive Content Intelligence (ASCI) team creates policies and builds services and tools through Machine Learning techniques to detect and mitigate sensitive content across Alexa.
In this role, you will work on essential backend operations that help maintain the quality and accuracy of our AI initiatives. This role involves basic data tasks, such as creating, reviewing, and managing test data sets. The ideal candidate is detail-oriented, willing to learn, and ready to contribute to the smooth operation of our team’s day-to-day tasks. You will perform quality audits and testing of datasets
Key job responsibilities
Key responsibilities:
* Test Data creation : Create test data sets and enable testing
* Review and Audits: Conduct audits to ensure accuracy, including extracting relevant information based on specified criteria.
* Quality Assurance: Deliver insights to enhance the precision of data-related processes.
* Data Handling: Work on large volumes of data with a focus on accuracy and ease of retrieval for use in AI-related activities.
* Process Metrics : Ensure high quality and high volume productivity
1. Bachelor’s degree
2. Experience in AI operations, data management, or similar roles within a technology-driven environment is preferred
3. Strong understanding of machine learning principles, algorithms, and methodologies.
4. Proficiency in programming languages such as Python, R, or similar, for data manipulation and analysis.
5. Experience with data annotation tools, and AI model testing frameworks.
6. Excellent analytical and problem-solving skills with a keen attention to detail.
7. Effective communication and collaboration skills to work cross-functionally and influence outcomes.
Experience in AI operations, data management, or similar roles within a technology-driven environment is preferred
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