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Llm Annotation Jobs in New Rochelle, NY (NOW HIRING)

Infotech Sourcing

Linguist III

Manhattan, NY · Remote

Write and revise guidelines for human annotation and other AI projects, including but not limited ... Preferably no known conflicts of interest in the fields of machine translation, ASR, TTS, or LLM ...

Mercor

Software Engineer, Agents

New York, NY · On-site

$130K - $500K/yr

Agents/LLM : LangGraph, LangChain, FastMCP, Harbor, NemoGym * Observability : Datadog, PostHog ... Studio - We own Mercor's evaluation system & annotation platform for RL environments and tasks. We ...

Meta

Product Content Engineer

New York, NY

$193K/yr

Drive sprints for LLM model evaluations and auto judge creation in core PCE areas, while devising ... engineering, annotation, and/or content labeling and analysis * Expertise in developing and ...

Semantix

Enterprise Solutions AI Consultant

New York, NY · On-site

... annotation, and generative AI services-to Fortune 500 leaders. TransPerfect AI offers a premier product suite that addresses the most critical bottlenecks in the AI lifecycle, from LLM fine-tuning to ...

Service Global, Inc

Linguist III

New York, NY · On-site

Write and revise guidelines for human annotation and other AI projects, including but not limited ... Preferably no known conflicts of interest in the fields of machine translation, ASR, TTS, or LLM ...

Semantix

Enterprise Solutions AI Consultant

New York, NY · On-site

... annotation, and generative AI services-to Fortune 500 leaders. TransPerfect AI offers a premier product suite that addresses the most critical bottlenecks in the AI lifecycle, from LLM fine-tuning to ...

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Showing results 21-40

All JobsLlm Annotation JobsLlm Annotation Jobs in New Rochelle, NY

Llm Annotation information

See New Rochelle, NY salary details

$11.3K

$42.7K

How much do llm annotation jobs pay per year?

As of Aug 23, 2026, the average yearly pay for llm annotation in New Rochelle, NY is $41,162.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,200.00 and $41,200.00 per year, depending on experience, location, and employer.

What is LLM annotation?

LLM annotation refers to the process of labeling or tagging data specifically for training and evaluating large language models (LLMs) like GPT or BERT. Annotators read text and apply labels, correct errors, or provide feedback to help improve the model's understanding and performance. This work is crucial for supervised learning, as well-annotated datasets help LLMs better recognize patterns, context, and meaning in human language. LLM annotation can involve tasks such as sentiment analysis, named entity recognition, or instruction following. Annotators often use specialized platforms or tools to complete their tasks efficiently and accurately.

What are the key skills and qualifications needed to thrive as an LLM annotation specialist?

To thrive as an LLM Annotation Specialist, you need strong analytical skills, attention to detail, and a background in linguistics, computer science, or a related field. Familiarity with annotation platforms, natural language processing (NLP) tools, and data labeling systems is typically required. Excellent communication, critical thinking, and the ability to follow guidelines precisely are valuable soft skills for this role. These skills ensure high-quality, accurate data annotation, which directly impacts the performance and reliability of large language models.

What are some common challenges faced by LLM annotation specialists, and how can they be addressed?

LLM Annotation specialists often encounter challenges such as interpreting ambiguous language data, maintaining annotation consistency across complex datasets, and keeping up with evolving guidelines. These can be addressed by participating in regular team syncs to clarify guidelines, using annotation tools with built-in quality checks, and collaborating closely with project leads and fellow annotators. Continuous learning and open communication help ensure high-quality, reliable data annotation and support professional growth within the AI and NLP fields.

What is the difference between Llm Annotation vs Data Labeler?

AspectLlm AnnotationData Labeler
Required CredentialsBasic computer skills, sometimes familiarity with AI toolsBasic skills, often on-the-job training
Work EnvironmentRemote or office-based, tech-focusedRemote or on-site, varied industries
Industry UsageAI, machine learning, NLP projectsVarious industries including marketing, healthcare, and tech
Search & Comparison IntentUnderstanding roles in AI data preparationGeneral data labeling tasks

In summary, Llm Annotation involves specialized annotation for large language models, often requiring familiarity with AI tools, while Data Labeler is a broader role focused on labeling data across multiple industries with minimal technical requirements.

How to become an Llm annotator?

To become an LLM annotator, candidates typically need strong language skills, attention to detail, and familiarity with data annotation tools. Many positions require a high school diploma or equivalent, and some companies provide training. Experience with machine learning or natural language processing can be beneficial but is not always necessary.

What are popular job titles related to Llm Annotation jobs in New Rochelle, NY?

For Llm Annotation jobs in New Rochelle, NY, the most frequently searched job titles are:

What cities near New Rochelle, NY are hiring for Llm Annotation jobs?

Cities near New Rochelle, NY with the most Llm Annotation job openings:

Llm Annotation jobs near you
Infographic showing various Llm Annotation job openings in New Rochelle, NY as of June 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 77% Physical, 5% Hybrid, and 18% Remote job distribution, with an average salary of $41,162 per year, or $19.8 per hour.

Linguist III

Infotech Sourcing

Manhattan, NY • Remote

Full-time

Posted 11 days ago

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)

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