Company:
Amazon TA
Location: London
Closing Date: 07/11/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
The Conversational Shopping team is looking for a Senior Language Engineer to drive efficiencies and innovation in its efforts to deliver a seamless, fluent, and multi-lingual experience for AI-assisted shopping. This is an opportunity to join the high-performing team behind Amazon’s Generative AI shopping initiatives. Our objective is to make it easy for customers worldwide to find and discover the best products, meet their unique needs with product research, providing comparisons and recommendations, answering specific product questions, and more. This role is inherently high-visibility and highly cross-functional, requiring collaboration and influence across global product, design, science, and engineering teams.
We are looking for candidates who are passionate about the intersection of language and technology and who are keen to develop scalable solutions to questions in the Large Language Model (LLM) space. Applying a combination of linguistic (i.e., semantics, syntax, pragmatics) and scripting expertise, they will overcome complex problems in natural language processing and language understanding.
This role, within International Editorial team, will design processes to facilitate the production of high quality editorial data which will allow us to evaluate and improve the Shopping AI experience in different languages. To do so, they will be tasked with the creation of enabling tools, automation scripts and automated annotations. They will lead and own the creation of the data annotation workflow, writing intuitive and labeler-friendly annotation guidelines. They will employ their data wrangling and analysis skills to measure team productivity and output quality. They will use their ability to create specification frameworks and templates for content editing and labeling to improve team workflows. They will work in close collaboration with Language Editors, Product Managers, Applied Scientists and Software Engineers on initiatives that drive editorial quality and consistency. By creating and synthesizing quality metrics, they will also guide Conversational Shopping teams in delivering both internal stakeholder requirements and achieve the desired Amazon customer outcomes.
This role requires strong analytical skills and language technology experience to help us measure, analyze and solve complex problems. They should have experience in automating and processing data workflows at scale and have the ability to do so while upholding the highest linguistic quality standards. They should also have exceptional writing and communication skills with the ability to interface between both technical and non-technical teams.
Key job responsibilities * Design and lead editorial data production/collection by defining scope with internal customer teams * Define clear editorial workflows (SOPs) to meet or exceed the quality bar * Adopt and design control mechanisms, metrics and methodologies for editorial and annotation quality * Maximize productivity, process efficiency and quality through streamlined workflows, process standardization, documentation, audits and investigations on a periodic basis. * Produce, process and manipulate different types of language data, analyze, and provide efficient solutions * Automate operations and perform data analysis using scripting language (e.g. Python) * Collaborate with editors, applied scientists, engineers, and product managers to deliver the optimal customer experience and define metrics, guidelines, and workflows to continue doing so * Establish processes and mechanisms to onboard and train editors on an ongoing basis. * Handle work prioritization and deliver based on business priorities. * Be flexible in changes to conventions deployed in response to customers’ requests and change workflows accordingly.
BASIC QUALIFICATIONS
* Bachelor’s or Master’s Degree in Applied Linguistics, Computational Linguistics, Natural Language Processing (NLP), or other related field. * Strong Experience in Natural Language Processing, Machine Learning, or Large Language Models * Proficient in Python. * Knowledge of Regex, SQL, MS Excel, Git. * Ability to navigate a Unix terminal and use common command line tools. * Familiarity with annotation tools and workflows. * Excellent communication and strong organizational skills with a keen eye for details. * Comfortable working in a fast-paced, collaborative, and dynamic work environment. * Willingness to support several projects at one time and to accept reprioritization as necessary.
PREFERRED QUALIFICATIONS
* Master’s Degree or PhD in Applied Linguistics, Computational Linguistics, Natural Language Processing (NLP), or other related technical field. * Proficient in French, German, Hindi, Italian, Spanish, or Japanese. * Experience in data science and quantitative research. * Experience with language annotation and other forms of data markup. * Hands-on experience with machine learning and deep learning techniques in the fields of NLP and search. * Experience with AWS services (S3, Sagemaker, ML language services, etc.). * Knowledge of user experience concepts and methods. * Familiarity with online retail (e-commerce).
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ((url removed)) to know more about how we collect, use and transfer the personal data of our candidates.
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 (url removed)
We are looking for candidates who are passionate about the intersection of language and technology and who are keen to develop scalable solutions to questions in the Large Language Model (LLM) space. Applying a combination of linguistic (i.e., semantics, syntax, pragmatics) and scripting expertise, they will overcome complex problems in natural language processing and language understanding.
This role, within International Editorial team, will design processes to facilitate the production of high quality editorial data which will allow us to evaluate and improve the Shopping AI experience in different languages. To do so, they will be tasked with the creation of enabling tools, automation scripts and automated annotations. They will lead and own the creation of the data annotation workflow, writing intuitive and labeler-friendly annotation guidelines. They will employ their data wrangling and analysis skills to measure team productivity and output quality. They will use their ability to create specification frameworks and templates for content editing and labeling to improve team workflows. They will work in close collaboration with Language Editors, Product Managers, Applied Scientists and Software Engineers on initiatives that drive editorial quality and consistency. By creating and synthesizing quality metrics, they will also guide Conversational Shopping teams in delivering both internal stakeholder requirements and achieve the desired Amazon customer outcomes.
This role requires strong analytical skills and language technology experience to help us measure, analyze and solve complex problems. They should have experience in automating and processing data workflows at scale and have the ability to do so while upholding the highest linguistic quality standards. They should also have exceptional writing and communication skills with the ability to interface between both technical and non-technical teams.
Key job responsibilities * Design and lead editorial data production/collection by defining scope with internal customer teams * Define clear editorial workflows (SOPs) to meet or exceed the quality bar * Adopt and design control mechanisms, metrics and methodologies for editorial and annotation quality * Maximize productivity, process efficiency and quality through streamlined workflows, process standardization, documentation, audits and investigations on a periodic basis. * Produce, process and manipulate different types of language data, analyze, and provide efficient solutions * Automate operations and perform data analysis using scripting language (e.g. Python) * Collaborate with editors, applied scientists, engineers, and product managers to deliver the optimal customer experience and define metrics, guidelines, and workflows to continue doing so * Establish processes and mechanisms to onboard and train editors on an ongoing basis. * Handle work prioritization and deliver based on business priorities. * Be flexible in changes to conventions deployed in response to customers’ requests and change workflows accordingly.
BASIC QUALIFICATIONS
* Bachelor’s or Master’s Degree in Applied Linguistics, Computational Linguistics, Natural Language Processing (NLP), or other related field. * Strong Experience in Natural Language Processing, Machine Learning, or Large Language Models * Proficient in Python. * Knowledge of Regex, SQL, MS Excel, Git. * Ability to navigate a Unix terminal and use common command line tools. * Familiarity with annotation tools and workflows. * Excellent communication and strong organizational skills with a keen eye for details. * Comfortable working in a fast-paced, collaborative, and dynamic work environment. * Willingness to support several projects at one time and to accept reprioritization as necessary.
PREFERRED QUALIFICATIONS
* Master’s Degree or PhD in Applied Linguistics, Computational Linguistics, Natural Language Processing (NLP), or other related technical field. * Proficient in French, German, Hindi, Italian, Spanish, or Japanese. * Experience in data science and quantitative research. * Experience with language annotation and other forms of data markup. * Hands-on experience with machine learning and deep learning techniques in the fields of NLP and search. * Experience with AWS services (S3, Sagemaker, ML language services, etc.). * Knowledge of user experience concepts and methods. * Familiarity with online retail (e-commerce).
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ((url removed)) to know more about how we collect, use and transfer the personal data of our candidates.
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 (url removed)
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Amazon TA