Job Role: Language Engineer, Search AI Data, Amazon

Location: Bangalore ,India

Years of Experience: 5+ years

Job Details: 

  • 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 and engineers in defining metrics, guidelines, and workflows.
  • Initiate and contribute towards improvement projects, present solution proposals, and implement them.
  • Onboard and train junior data associates on an ongoing basis.
  • Handle work prioritization and deliver based on business needs.
  • Be flexible in changes to conventions deployed in response to customers’ requests and change workflows accordingly.

Job Description:

Amazon Search AI Data Team is looking for an experienced Language engineer. The mission of the Search Data Platform team is to build an end-to-end data platform to deliver high quality datasets at scale. The team owns the systems and pipelines that enable data acquisition, ingestion, classification, visualization, human annotation, training, evaluation, and active learning.

Search AI Data is part of the Amazon Core Search organization which owns search functionality, the main discovery mechanism for customers shopping on Amazon worldwide. It is responsible for (a) research, development, and operation of the search customer experience for apps and websites (recommendation widgets, refinements, whole page optimization, rendering, autocomplete); (b) search services for physical and digital items (data ingestion, natural language processing, index generation, query serving); (c) site reliability engineering and compute capacity management for all search services; (d) search economics and search performance data science. In addition, we collaborate closely with several machine learning (ML) applied science teams that develop and test ML models to improve the quality of semantic matching, ranking, computer vision, image processing, and augmented reality.

Mandatory Qualifications:

  • Bachelor’s or Master’s Degree in Linguistics, Computational Linguistics, Natural Language Processing (NLP), or other related field.
  • Relevant work experience of 5+ years.
  • 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.
  • Experience in data science and quantitative research.
  • 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).

About Amazon:

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to be Earth’s most customer-centric company, Earth’s best employer, and Earth’s safest place to work. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology, Amazon Studios, and The Climate Pledge are some of the things pioneered by Amazon.

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