Language Engineer , AWS AI Data | Transcribe

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Job summary
The AI Data Team in Amazon Web Services (AWS) is looking for a forward-looking and 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, New York City, or Seattle.

The mission of the AI Data Team is to engineer language datasets and artifacts critical to the success of AWS’s machine learning services. From subtitles to text analytics to chatbots 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 contact center analytics for Contact Lens and Transcribe. You will analyze, follow, and improve established processes for collecting and annotating natural language data from a variety of sources and in multiple languages, 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 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.

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. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

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.

Notes
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Workers in New York City who perform in-person work or interact with the public in the course of business must show proof they have been fully vaccinated against COVID or request and receive approval for a reasonable accommodation, including medical or religious accommodation.

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
The AI Data Team at AWS is responsible for delivering high-quality annotated data and a variety of language artifacts to ensure the best performance of different AWS machine-learning language services. These ML-based language services enable customers to readily add intelligence to their business operations and AI applications to drive positive outcomes.

BASIC QUALIFICATIONS

• PhD in Computational Linguistics, Linguistics with a computational component, or an equivalent field.
• Excellent knowledge on semantics, pragmatics, conversation analysis, and/or discourse analysis.
• 2+ years experience in the field.
• Proficiency in scripting and analytics tools such as Python, R, SQL, or similar.
• Experience building ontologies, taxonomies, and other semantic relation frameworks.
• Experience owning and executing language data collection and annotation projects with data quality assessments.
• Ability to explain complex concepts and solutions in easy-to-understand terms.
• Flexibility to work in a fast paced, highly collaborative and dynamic work environment.

PREFERRED QUALIFICATIONS

• Willingness to support several projects at one time and to accept reprioritization as necessary.
• Practical knowledge of version control systems such as GitHub.
• Experience working with speech and text language data in a multiple languages or language varieties.
• Fluency in one or more of these languages: Spanish, French, Italian, German, Korean, Japanese, Hindi.