Language Engineer II, Amazon Transcribe

The Amazon Transcribe Data Team in Amazon Web Services (AWS) is looking for a forward-looking and collaborative Language Engineer II to join us in developing solutions for natural language data collections. This position is an opportunity to apply your expertise in a challenging but supportive environment.

The mission of the Amazon Transcribe Data Team is to engineer the datasets critical to the success of GenAI services for Amazon Transcribe. From chatbots to subtitles to search results and beyond, these products support dozens of languages and impact millions of people every day. We are a group of language engineers, linguists, data scientists, data engineers, and program managers, and we partner closely with science, engineering, and product teams. We are customer obsessed and committed to delivering results with the highest quality and integrity.

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.
- Collaborate with stakeholders to design and oversee data collection and development efforts.
- 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.

About the team
This team is part of AWS Utility Computing:

Utility Computing (UC)
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 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.

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.


- 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

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.