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As a Language Engineer, you will start by diving deep into a couple of critical projects for Bedrock services to drive these projects forward. You will collaborate with fellow language engineers, program managers, as well as stakeholders in science, engineering, and product teams to understand the role data plays in developing models that meet customer needs. You will analyze, follow, and improve processes for collecting and annotating LLM inputs and outputs, 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 pipeline. You will apply state-of-the-art Generative AI 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- Oversee the progress and quality of several data collection and annotation projects at a time
- Advocate for strict adherence to data collection guidelines and quality thresholds
- Extend existing data collection, annotation, and quality assurance efforts to support feature and language expansion
- Innovate on data collection methodologies, guidelines, quality metrics to support new requests
- Automate repetitive workflows and improve existing processesA day in the life
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.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
- 2+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- PhD in Computational Linguistics, Linguistics with a computational component, or an equivalent field; alternatively, MA/MS with 3+ years of experience
- Excellent knowledge of semantics, pragmatics, conversation analysis, and/or discourse analysis
- Experience designing and executing data collection projects, including guidelines, labelset and annotation workflow development
- Experience developing and evaluating data annotation and data quality metrics
- Experience designing and executing psychology/linguistic/cognitive science surveys or experiments with human participants
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