Computational Linguist

About the Project:

We are embarking on an ambitious project to develop cutting-edge language technologies, including Large Language Models (LLMs), Automatic Speech Recognition (ASR), and Text-to-Speech (TTS) systems, for 22 diverse Indian languages. We are seeking a highly skilled and motivated Computational Linguist to join our team and play a crucial role in shaping the future of multilingual AI.

Job Summary:

The Computational Linguist Intern/Contractor will be responsible for providing linguistic expertise and support to the development and improvement of our LLM, ASR, and TTS models across a wide range of Indian languages. This role will involve analyzing linguistic data, creating resources, and collaborating with machine learning engineers to enhance the accuracy and naturalness of our language technologies.

Responsibilities:

1.Research aspect

• Collaborate with machine learning engineers to integrate linguistic knowledge into model development.
• Identify and address linguistic challenges related to the development of LLMs, ASR, and TTS systems, such as dialectal variations, low-resource languages, data composition of pretraining data.
• Design, execute pilot experiments for data synthesis, exploratory data analysis and analyze results
• Evaluate the linguistic quality of model outputs and provide feedback for improvement.

2.Implementation aspect

• Develop and adapt linguistic tools and techniques for data processing and analysis.

Qualifications and Experience:

1.Education:

• PhD in Computational Linguistics

2.Experience:

• Professional experience: prior professional experience is not strictly required. However, relevant academic or project experience, like Experience with developing or evaluating NLP tools or systems like TTS is highly desirable.
• Research Experience: Experience with linguistic research, data analysis, or experimental design is a plus.
• Programming/Scripting: Expertise in programming or scripting languages (e.g. Python), especially for data processing and tool development.
• Experience working with low resource languages is a plus.

Preferred 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.
• Research Skills: Ability to conduct research, design experiments, and analyze results is a plus

Note:

• Publications or Presentations: Publications or presentations at relevant conferences or journals are a plus.