Amazon Language Engineer II Amazon Transcribe 

United States, Virginia 

22316797

As a Language Engineer, you will start by diving deep into a high profile project to launch a new product offering. You will consult with stakeholders in science, engineering, and product teams to strategize on data collection and annotation. You will analyze, follow, and improve processes for annotating transcribed conversations, assessing data quality and automating where appropriate.You will then expand your scope by using the principles of data-centric AI to understand the role our data plays with regard to model performance specifically, as well as the larger ML pipelines. You will apply state-of-the-art ML and NLP techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other language engineers and scientists to design and implement principled strategies for data optimization.Key job responsibilities
- Source, validate, and deliver high-quality language artifacts and linguistic data.- Innovate on data collection methodologies, guidelines, quality metrics to support new requests.
- Extend existing data collection and annotation efforts to support feature and language expansion.
- Automate repetitive workflows and improve existing processes.
Utility Computing (UC)
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred 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.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

- PhD or Masters in Computational Linguistics, Linguistics with a computational component, or an equivalent field
- Excellent knowledge of semantics, pragmatics, conversation analysis, and/or discourse analysis
- Experience owning and executing language data collection projects, including guidelines, labelset and annotation workflow development
- Proficiency in Python and other analytics tools such as R to process and analyze language data
- Experience in developing and evaluating data annotation and data quality metrics

- Ability to explain complex concepts and solutions in easy-to-understand terms
- Experience building ontologies, taxonomies, and other semantic relation frameworks
- Practical knowledge of version control systems such as GitHub