Linguist III
PR · Remote
US - NY - Remote Duration:8 months Job Title: Linguist lII (FAIR) Main duties: Perform linguistic ... Write and revise guidelines for human annotation and other AI projects, including but not limited ...
Linguist III
PR · Remote
US - NY - Remote Duration:8 months Job Title: Linguist lII (FAIR) Main duties: Perform linguistic ... Write and revise guidelines for human annotation and other AI projects, including but not limited ...
Internship Remote Data Annotation information
What are the key skills and qualifications needed to thrive as a Remote Data Annotation Intern, and why are they important?
To thrive as a Remote Data Annotation Intern, you need attention to detail, basic data processing skills, and familiarity with labeling guidelines, generally supported by a high school diploma or relevant coursework. Experience with annotation platforms, spreadsheets, and sometimes basic programming tools or machine learning frameworks is often required. Strong communication, time management, and the ability to follow precise instructions are valuable soft skills in this role. These skills ensure high-quality, accurate data labeling, which is critical for training reliable machine learning models.
What typical tasks can I expect to handle as a remote data annotation intern, and how is performance usually evaluated?
As a remote data annotation intern, your primary tasks will involve reviewing and labeling data—such as images, text, or audio—according to specific guidelines provided by your team. You'll likely work with annotation tools, follow detailed instructions to ensure high-quality and consistent labeling, and may participate in quality assurance checks. Performance is generally evaluated based on annotation accuracy, speed, and your ability to follow instructions, with regular feedback provided via virtual meetings or project management platforms. Effective communication and attention to detail are key to succeeding in this collaborative, remote environment.
What is a remote data annotation internship?
A remote data annotation internship is a temporary position where interns work from home or another remote location to label, categorize, or tag data such as images, text, or audio. This annotated data is often used to train machine learning models and improve artificial intelligence systems. Interns typically use specialized platforms or tools to complete their tasks, and gain hands-on experience in data handling, quality control, and understanding AI workflows. The internship is ideal for those interested in technology, data science, or AI, and often requires strong attention to detail and good communication skills.
What is the difference between Internship Remote Data Annotation vs Data Labeling Specialist?
| Aspect | Internship Remote Data Annotation | Data Labeling Specialist |
|---|---|---|
| Credentials | Typically students or entry-level with basic computer skills | Relevant experience or certifications in data annotation or related fields |
| Work Environment | Remote, flexible hours, often part-time | Remote or on-site, depending on employer, often full-time |
| Industry Usage | Common in AI/ML projects, tech companies, research institutions | Used in AI/ML, autonomous vehicles, healthcare, and tech sectors |
Internship Remote Data Annotation roles are usually entry-level, temporary positions aimed at gaining experience, while Data Labeling Specialists are more experienced roles focused on accurately annotating data for machine learning models. Both roles are essential in AI development but differ in experience requirements and job scope.
What are the most commonly searched types of Remote Data Annotation jobs in Puerto Rico? The most popular types of Remote Data Annotation jobs in Puerto Rico are:
What are popular job titles related to Internship Remote Data Annotation jobs in Puerto Rico? For Internship Remote Data Annotation jobs in Puerto Rico, the most frequently searched job titles are:
What job categories do people searching Internship Remote Data Annotation jobs in Puerto Rico look for? The top searched job categories for Internship Remote Data Annotation jobs in Puerto Rico are:
What cities in Puerto Rico are hiring for Internship Remote Data Annotation jobs? Cities in Puerto Rico with the most Internship Remote Data Annotation job openings:
Job description
Job Title: Infrastructure Engineering - Linguist III
Location: US - NY - Remote
Duration:8 months
Job Title: Linguist lII (FAIR)
Main duties:
Perform linguistic analyses on large datasets.
Perform linguistic error analysis of AI model outputs, determining what the most frequent and severe error categories are.
Write and revise guidelines for human annotation and other AI projects, including but not limited to translation tasks.
Conduct typological and sociolinguistic research on a large number of languages, highlighting their similarities and differences.
Perform linguistic analyses for Responsible AI (toxic language, hate speech, gender bias and other cultural biases) in massively multilingual settings.
Conduct linguistic literature reviews on various NLP-adjacent topics, and summarize findings.
Compare the quality of deliveries between vendors, identify error patterns, and provide actionable feedback.
Provide information or guidance relative to any aspect of linguistic knowledge (typology, morpho-syntax, sociolinguistics, classification, phonetics/phonology, pragmatics, etc.).
Reach out to and collaborate with native speakers in various languages.
Communicate results of linguistic analyses to engineers and research scientists.
Skills:
Must have strong written and spoken communication skills, especially business and research communication.
Must be a native speaker of a non-English language (preferably Hindi) with a high level of proficiency in another Indo-Aryan or South Dravidian language, plus broad knowledge of other languages in either of those two groups.
Working knowledge in other languages is a plus. Proficiency in a low-resource language is valued.
Must be able to code in Python (must) and query databases using SQL, other coding languages used for data analysis are a plus.
Must be able to independently work through complex requests and perform under pressure.
Strong ability to work independently, prioritize, plan, and track work, as well as report progress
education or training in the basics of project management is a plus
self-motivation is a must
Working knowledge of international language-classification standards is valued.
Education:
Graduate degree in Linguistics or related field is a must; PhD is a plus
a background or specialization in corpus linguistics is a plus
experience with field work is a plus
a graduate degree in Literature or English is not an appropriate substitution
degree in Computer Science with a specialization in NLP is not an appropriate substitution
Must have a very firm grasp of the following linguistic fields: language typology, syntax, morphology, sociolinguistics (especially dialectology and discourse analysis), corpus linguistics, writing systems, pragmatics, phonology.
Must have some experience with applying basic Natural Language Processing techniques.
Experience
Years of experience: 0-3
Experience working cross-functionally
Experience collaborating with machine learning, NLP, or software engineers, or data scientists
Experience contributing to research papers
Important: Preferably no known conflicts of interest in the fields of machine translation, ASR, TTS, or LLM research (as FAIR Linguists need to be contributing to research papers)
Location: US - NY - Remote
Duration:8 months
Job Title: Linguist lII (FAIR)
Main duties:
Perform linguistic analyses on large datasets.
Perform linguistic error analysis of AI model outputs, determining what the most frequent and severe error categories are.
Write and revise guidelines for human annotation and other AI projects, including but not limited to translation tasks.
Conduct typological and sociolinguistic research on a large number of languages, highlighting their similarities and differences.
Perform linguistic analyses for Responsible AI (toxic language, hate speech, gender bias and other cultural biases) in massively multilingual settings.
Conduct linguistic literature reviews on various NLP-adjacent topics, and summarize findings.
Compare the quality of deliveries between vendors, identify error patterns, and provide actionable feedback.
Provide information or guidance relative to any aspect of linguistic knowledge (typology, morpho-syntax, sociolinguistics, classification, phonetics/phonology, pragmatics, etc.).
Reach out to and collaborate with native speakers in various languages.
Communicate results of linguistic analyses to engineers and research scientists.
Skills:
Must have strong written and spoken communication skills, especially business and research communication.
Must be a native speaker of a non-English language (preferably Hindi) with a high level of proficiency in another Indo-Aryan or South Dravidian language, plus broad knowledge of other languages in either of those two groups.
Working knowledge in other languages is a plus. Proficiency in a low-resource language is valued.
Must be able to code in Python (must) and query databases using SQL, other coding languages used for data analysis are a plus.
Must be able to independently work through complex requests and perform under pressure.
Strong ability to work independently, prioritize, plan, and track work, as well as report progress
education or training in the basics of project management is a plus
self-motivation is a must
Working knowledge of international language-classification standards is valued.
Education:
Graduate degree in Linguistics or related field is a must; PhD is a plus
a background or specialization in corpus linguistics is a plus
experience with field work is a plus
a graduate degree in Literature or English is not an appropriate substitution
degree in Computer Science with a specialization in NLP is not an appropriate substitution
Must have a very firm grasp of the following linguistic fields: language typology, syntax, morphology, sociolinguistics (especially dialectology and discourse analysis), corpus linguistics, writing systems, pragmatics, phonology.
Must have some experience with applying basic Natural Language Processing techniques.
Experience
Years of experience: 0-3
Experience working cross-functionally
Experience collaborating with machine learning, NLP, or software engineers, or data scientists
Experience contributing to research papers
Important: Preferably no known conflicts of interest in the fields of machine translation, ASR, TTS, or LLM research (as FAIR Linguists need to be contributing to research papers)
About Infotech Sourcing
Sourced by ZipRecruiter
Industry
It services
Company size
11 - 50 Employees
Headquarters location
San Francisco, CA, US
Year founded
2004