The Conversational Shopping team is looking for a SeniorLanguage Engineer to drive efficiencies and innovation in itsefforts to deliver a seamless, fluent, and multi-lingual experiencefor AI-assisted shopping.
This is an opportunity to join thehigh-performing team behind Amazon's Generative AI shoppinginitiatives.
Our objective is to make it easy for customersworldwide to find and discover the best products, meet their uniqueneeds with product research, providing comparisons andrecommendations, answering specific product questions, and more.This role is inherently high-visibility and highlycross-functional, requiring collaboration and influence acrossglobal product, design, science, and engineeringteams.
We are looking for candidates who arepassionate about the intersection of language and technology andwho are keen to develop scalable solutions to questions in theLarge Language Model (LLM) space.
Applying a combination oflinguistic (i.e., semantics, syntax, pragmatics) and scriptingexpertise, they will overcome complex problems in natural languageprocessing and language understanding.
Thisrole, within International Editorial team, will design processes tofacilitate the production of high quality editorial data which willallow us to evaluate and improve the Shopping AI experience indifferent languages.
To do so, they will be tasked with thecreation of enabling tools, automation scripts and automatedannotations.
They will lead and own the creation of the dataannotation workflow, writing intuitive and labeler-friendlyannotation guidelines.
They will employ their data wrangling andanalysis skills to measure team productivity and output quality.They will use their ability to create specification frameworks andtemplates for content editing and labeling to improve teamworkflows.
They will work in close collaboration with LanguageEditors, Product Managers, Applied Scientists and SoftwareEngineers on initiatives that drive editorial quality andconsistency.
By creating and synthesizing quality metrics, theywill also guide Conversational Shopping teams in delivering bothinternal stakeholder requirements and achieve the desired Amazoncustomer outcomes.
This role requires stronganalytical skills and language technology experience to help usmeasure, analyze and solve complex problems.
They should haveexperience in automating and processing data workflows at scale andhave the ability to do so while upholding the highest linguisticquality standards.
They should also have exceptional writing andcommunication skills with the ability to interface between bothtechnical and non-technical teams.
Key jobresponsibilities Design and lead editorial dataproduction/collection by defining scope with internal customerteams Define clear editorial workflows (SOPs) to meetor exceed the quality bar Adopt and design controlmechanisms, metrics and methodologies for editorial and annotationquality Maximize productivity, process efficiency andquality through streamlined workflows, process standardization,documentation, audits and investigations on a periodicbasis.
Produce, process and manipulate different typesof language data, analyze, and provide efficientsolutions Automate operations and perform data analysisusing scripting language (e.g.
Python) Collaborate witheditors, applied scientists, engineers, and product managers todeliver the optimal customer experience and define metrics,guidelines, and workflows to continue doing so Establish processes and mechanisms to onboard and train editors onan ongoing basis.
Handle work prioritization anddeliver based on business priorities.
Be flexible inchanges to conventions deployed in response to customers' requestsand change workflows accordingly.
BASICQUALIFICATIONS Bachelor's or Master's Degree in AppliedLinguistics, Computational Linguistics, Natural Language Processing(NLP), or other related field.
Strong Experience inNatural Language Processing, Machine Learning, or Large LanguageModels Proficient in Python.
Knowledge ofRegex, SQL, MS Excel, Git.
Ability to navigate a Unixterminal and use common command line tools.
Familiaritywith annotation tools and workflows.
Excellentcommunication and strong organizational skills with a keen eye fordetails.
Comfortable working in a fast-paced,collaborative, and dynamic work environment.
Willingness to support several projects at one time and to acceptreprioritization as necessary.
PREFERREDQUALIFICATIONS Master's Degree or PhD in AppliedLinguistics, Computational Linguistics, Natural Language Processing(NLP), or other related technical field.
Proficient inFrench, German, Hindi, Italian, Spanish, or Japanese.
Experience in data science and quantitative research.
Experience with language annotation and other forms of datamarkup.
Hands-on experience with machine learning anddeep learning techniques in the fields of NLP andsearch.
Experience with AWS services (S3, Sagemaker, MLlanguage services, etc.).
Knowledge of user experienceconcepts and methods.
Familiarity with online retail(e-commerce).
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