Language Resource Manager

Job Summary

We are looking for Linguistics experts with team management experience, extensive experience working on NLP projects and proficiency in 2 or more languages from any one of the following language groups:

• Bengali, Oriya, Assamese, Bodo, Manipuri
• Kannada, Malayalam, Tamil, Telugu
• Hindi, Maithili, Urdu, Dogri, Kashmiri, Punjabi, Gujarati

The Language Resource Manager will have two-fold responsibility:

• Support development and improvement of our LLM, ASR, and TTS models by providing linguistic expertise
• Manage the work of freelancing language resources for the assigned group of languages.

Key Responsibilities

• Linguistic support

-Collaborate with machine learning engineers to understand data requirements and to identify opportunities to integrate linguistic knowledge into model development

-Create guidelines for data annotation/validation projects based on data requirements

-Evaluate the linguistic quality of model outputs and provide feedback for improvement

• Management

-Collaborate with data sourcing team to understand data processing timelines and operational constraints

-Set up operational pipelines for processing sourced data and delivering processed data to model development team

-Source freelancing resources for various tasks for languages from the assigned language group, assign them data annotation task and track and manage their work

Education Qualifications & Experience

• Master's or PhD in Linguistics or Computational Linguistics.
• At least 3 years of experience working on NLP projects, providing language data annotation for Machine Learning or GenAI projects.
• Experience creating guidelines to be followed by language resources preferred.
• Project co-ordination experience with 2+ years of team/project management experience preferred.
• Experience working with low resource languages is a plus.

Technical Skills:

• Linguistic Analysis: Strong understanding of linguistic principles and the ability to analyze linguistic data.
• Problem-Solving: Ability to identify and solve linguistic challenges related to language technology.
• Collaboration: Excellent communication and collaboration skills to work effectively with machine learning engineers and other team members.
• Management: Ability to set up processes and pipelines, track and manage work of language resources