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Company:
Smart Communications group
Posted: June 8, 2024
Global Leader in Turnkey, Integration, Supply Chain, Field Deployment & Support Services. Iron Is Not Just A Great Place to Work. but a Place to do Great Work! Let's Work Together and Explore Opportunities
Join a success-oriented, talented team of individuals
Get best of training, compensation and benefit packages
Iron Systems is an innovative, customer-focused provider of custom-built computing infrastructure platforms such as network servers, storage, OEM/ODM appliances & embedded systems. For more than 15 years, customer have trusted us for our innovative problem solving combined with holistic design, engineering, manufacturing, logistic and global support services.
Job Title:
Linguist III
Location:
Redmond WA
Summary:
We are looking for a skilled linguistic Engineer to join our team and maintain the data in our LLM data grading and analysis pipelines.
In this role, you will be instrumental in assessing the quality of data processed by our LLM systems.
Using new and existing data quality workflows and pipelines, you will collaborate closely with a cross functional team of engineers, research scientists, project managers, and data scientists to report on and guide improvements on our LLM powered features, ensuring their accuracy and reliability in smart glasses applications.
Job Responsibilities:
Maintain production data grading queues, report on product and annotation quality, perform data analysis using SQL, Python, and spreadsheets.
Guide your analyses using linguistic expertise in the areas of phonetics, phonology, dialectology, and NLP.
Design and conduct experiments for evaluating rater quality, inter-rater reliability; write summary reports based on findings and speak on those findings in meetings.
Develop manual and automated processes for multiple concurrent projects ensuring high-quality labeled data.
Create and perfect LLM Quality grading queues and LLM related component quality error attribution grading queues.
Build datasets and write guidelines in rapid fashion for new and emergent LLM data rating, creation, and annotation needs.
Analyze system metrics such as factuality, brevity, coherence, as well as subcomponent performance, summarize findings, and communicate results.
This is not an annotator position, though annotation will occasionally be required to accommodate urgent requests.
Skills:
Basic Python, basic SQL with strong desire to grow required for this position. Intermediate level preferred.
Basic knowledge of linguistics (some of Phonetics, Syntax, Semantics, Dialectology) required.
Ability to analyze numerical rating results and draw conclusions based on data.
Basic stats / math for data analysis.
Written and oral communication skills necessary for communicating on project milestones and for reporting findings .
Education/Experience:
Bachelor's degree in computational linguistics, speech science, or related field OR graduate degree in linguistics OR industry similar experience required.
Master's degree or beyond preferred OR equivalent industry experience.
Additional learning via Coursera, Udemy, or other online resources great too.
•
Join a success-oriented, talented team of individuals
Get best of training, compensation and benefit packages
Iron Systems is an innovative, customer-focused provider of custom-built computing infrastructure platforms such as network servers, storage, OEM/ODM appliances & embedded systems. For more than 15 years, customer have trusted us for our innovative problem solving combined with holistic design, engineering, manufacturing, logistic and global support services.
Job Title:
Linguist III
Location:
Redmond WA
Summary:
We are looking for a skilled linguistic Engineer to join our team and maintain the data in our LLM data grading and analysis pipelines.
In this role, you will be instrumental in assessing the quality of data processed by our LLM systems.
Using new and existing data quality workflows and pipelines, you will collaborate closely with a cross functional team of engineers, research scientists, project managers, and data scientists to report on and guide improvements on our LLM powered features, ensuring their accuracy and reliability in smart glasses applications.
Job Responsibilities:
Maintain production data grading queues, report on product and annotation quality, perform data analysis using SQL, Python, and spreadsheets.
Guide your analyses using linguistic expertise in the areas of phonetics, phonology, dialectology, and NLP.
Design and conduct experiments for evaluating rater quality, inter-rater reliability; write summary reports based on findings and speak on those findings in meetings.
Develop manual and automated processes for multiple concurrent projects ensuring high-quality labeled data.
Create and perfect LLM Quality grading queues and LLM related component quality error attribution grading queues.
Build datasets and write guidelines in rapid fashion for new and emergent LLM data rating, creation, and annotation needs.
Analyze system metrics such as factuality, brevity, coherence, as well as subcomponent performance, summarize findings, and communicate results.
This is not an annotator position, though annotation will occasionally be required to accommodate urgent requests.
Skills:
Basic Python, basic SQL with strong desire to grow required for this position. Intermediate level preferred.
Basic knowledge of linguistics (some of Phonetics, Syntax, Semantics, Dialectology) required.
Ability to analyze numerical rating results and draw conclusions based on data.
Basic stats / math for data analysis.
Written and oral communication skills necessary for communicating on project milestones and for reporting findings .
Education/Experience:
Bachelor's degree in computational linguistics, speech science, or related field OR graduate degree in linguistics OR industry similar experience required.
Master's degree or beyond preferred OR equivalent industry experience.
Additional learning via Coursera, Udemy, or other online resources great too.
•
Read the full job description and apply online on the recuiter's web-site
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