Amazon.com Services LLC

Software Development, Language Engineer, Retail

LanguageEngineer,CoreSearch

$83–132k Seattle, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Language Engineer, Core Search at Amazon.com Services LLC. Skills: Language Engineering, Data Annotation, Natural Language Processing. Design data annotation guidelines. Develop data annotation guidelines”

What You'll Achieve.

Deliver on stakeholder requirements; Improve customer experience; Measure search quality; Produce metrics for AI models; Produce metrics for customer experience

Industry & Context.

Software Development, Language Engineer, Retail
Problems you'll solve

Problem solving

What They're Looking For.

Must Have

2+ years computational linguistics experience, 2+ years language data processing experience, 2+ years semantics experience, 2+ years philosophy of language experience, Master's degree in Linguistics, 5+ years relevant professional experience, Proficiency in Python, Knowledge of Regex, Knowledge of SQL, Knowledge of MS Excel, Knowledge of Git, Navigate Unix terminal, Use common command line tools, Familiarity with annotation tools, Familiarity with annotation workflows, Excellent communication skills, Excellent organizational skills, Keen eye for details, Comfortable in fast-paced environment, Comfortable in collaborative environment, Comfortable in dynamic work environment, Willingness to support several projects, Accept reprioritization as necessary

Nice to Have

Proficient in French, Proficient in German, Proficient in Dutch, Proficient in Italian, Proficient in Spanish, Proficient in Japanese, Experience in data science, Experience in quantitative research, Experience with language annotation, Experience with data markup, Hands-on ML experience, Hands-on DL experience, NLP experience, Search experience, Experience with AWS services, Knowledge of user experience concepts, Knowledge of user experience methods, Familiarity with online retail, Familiarity with e-commerce

What You'll Do.

Design data annotation guidelines

Develop data annotation guidelines

Design data annotation workflows

Develop data annotation workflows

Manage large amounts of data

Process large amounts of data

Adopt quality control metrics

Design quality control metrics

Evaluate data annotation quality

Maximize productivity

Maximize process efficiency

Standardize processes

Conduct investigations

Handle annotation requests

Handle data investigation requests

Deliver based on priorities

Be flexible in changes

Change workflows accordingly

Write annotation guidelines

Support data wrangling

Support data analysis

Define UI template specifications

Report data quality metrics

Train junior data associates

Onboard junior data associates

How You'll Work.

Team & Collaboration

Cross-functional teams; Global product teams; Global design teams; Global science teams; Global operations teams; Global engineering teams; Scientists; Engineers; Product managers

Communication Scope

Excellent communication

Full Job Description

We are the MIDAS team within the Amazon Search organization. We own the end-to-end human annotation requirements for our product partners. This is an opportunity to join a high-performing team that helps customers worldwide find and discover the best products, meet their personalized needs with the right product details, and receive comparisons, recommendations, and more on Amazon. This role is high-visibility and highly cross-functional, requiring collaboration and influence across global product, design, science, operations, and engineering teams. We are looking for a Language Engineer to join MIDAS to write intuitive, labeler-friendly annotation guidelines that enable measurement of search quality, support data wrangling and analysis, define specifications for labeling UI templates, and report labeled-data quality metrics to deliver on stakeholder requirements and improve the customer experience. To achieve high accuracy and consistency in labeled data outputs, Language Engineers apply linguistic (e.g., semantics, syntax, pragmatics) and scripting expertise to solve natural language processing and language understanding challenges. Key job responsibilities Design and develop data annotation guidelines and workflows. Manage and process large amounts of structured and unstructured data. Adopt and design quality control metrics and methodology to evaluate the quality of data annotation. Maximize productivity, process efficiency and quality through streamlined workflows, process standardization, documentation, audits and investigations on a periodic basis. Handle annotation & data investigation requests from multiple stakeholders with high efficiency and quality in a fast-paced environment. Collaborate with scientists, engineers, and product managers in defining metrics, guidelines, and workflows. Initiate and contribute towards improvement projects, present solution proposals, and implement them. Establish processes and mechanisms to onboard and train junior data as

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