- Masters in Computational Linguistics (or similar quantitative field), or equivalent experience
- Proficiency in scripting and analytics tools such as Python or R
- Experience with collecting and analyzing language data
Job summary
The AI Data Team in Amazon Web Services (AWS) is looking for a collaborative Language Engineer 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 position may be located in Santa Clara, Seattle, or New York City.
The mission of the AI Data Team is to engineer the datasets critical to the success of AWS’s machine learning services. 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 the 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 contributing to maintenance and expansion projects for Lex conversational AI and chatbots. You will understand and follow established processes for developing language artifacts such as grammars and catalogs, suggesting improvements and opportunities for automation where appropriate. You will participate in code reviews, help address customer-found defects, and improve vendor-facing guidelines.
You will then expand your scope by using the principles of data-centric AI to understand how well our data represents the wonderful variety of human language, both within and across locales. You will apply state-of-the-art ML and NLP techniques for classification and analysis, and you will work collaboratively with other language engineers and scientists to implement principled strategies for data optimization.
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Key job responsibilities
- Source, validate, and deliver high-quality language artifacts
- Automate repetitive workflows
- Understand our data and continuously work to improve and expand it
- Industry experience developing NLP products
- Basic understanding of the ML pipeline
- Experience working with a diverse array of languages or language varieties
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.