Amazon Web Services (AWS) is looking for a data associate to help with annotations, data analysis and quality assurance. 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.
This role will be responsible to lead training and provide continuous feedback for a vendor team.


Key job responsibilities
* Conduct regular training sessions, monitor performance, provide feedback, and analyze calibration tests results to identify trends, gaps in knowledge, and areas of improvement of the BDB Team.
* 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.
* 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.
* Collaborate with LEs, scientists, and Ops Manager to innovate processes, tracker automations, and workflows.

About the team
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.


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.

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.

Hybrid Work
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.