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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 data scientists, 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 data scientists 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 processesDiverse 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
Hybrid Work
Master’s degree in Linguistics, Computational Linguistics, or other language or data-related disciplines
2+ years experience with human data collection studies
Proficiency in Python
Experience with language data analysis
Experience with command-line environments (e.g. Unix) and version control (e.g. Git)
Experience in developing and evaluating data annotation metrics
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