Linguist III
New York, NY · On-site
... support services. Job Title: Linguist III Location: US - NY - Remote Main duties: * Perform ... Write and revise guidelines for human annotation and other AI projects, including but not limited ...
Linguist III
New York, NY · On-site
... support services. Job Title: Linguist III Location: US - NY - Remote Main duties: * Perform ... Write and revise guidelines for human annotation and other AI projects, including but not limited ...
Fullstack Engineer, RL Environments
New York, NY · On-site
$130K - $500K/yr
... services powering data pipelines and delivery of outputs to customers. You'll also build and ... Experience building tooling for data labeling, annotation, or human-in-the-loop AI workflows.
Fullstack Engineer, RL Environments
New York, NY · On-site
$130K - $500K/yr
... services powering data pipelines and delivery of outputs to customers. You'll also build and ... Experience building tooling for data labeling, annotation, or human-in-the-loop AI workflows.
Software Engineer, Agents
New York, NY · On-site
$130K - $500K/yr
We're a leading AI data company, building the layer between human expertise and frontier models ... Studio - We own Mercor's evaluation system & annotation platform for RL environments and tasks. We ...
Software Engineer, Agents
New York, NY · On-site
$130K - $500K/yr
We're a leading AI data company, building the layer between human expertise and frontier models ... Studio - We own Mercor's evaluation system & annotation platform for RL environments and tasks. We ...
... annotation and transfer of post processing image data to and from workstations situated in the ... Join us and experience the extensive resources and services designed to enhance your overall ...
... annotation and transfer of post processing image data to and from workstations situated in the ... Join us and experience the extensive resources and services designed to enhance your overall ...
Data Annotation Services information
What are the key skills and qualifications needed to thrive in data annotation services?
To excel in Data Annotation Services, strong attention to detail, data literacy, and a foundational understanding of data labeling processes are essential, often requiring a high school diploma or equivalent. Familiarity with annotation platforms, labeling tools, and sometimes basic knowledge of scripting or data management systems is typically expected. Strong work ethic, consistency, and effective communication skills help individuals stand out in collaborative, deadline-driven environments. These capabilities ensure high-quality, accurate labeled data, which is critical for training reliable machine learning models.
What is the difference between Data Annotation Services vs Data Labeling Specialists?
| Aspect | Data Annotation Services | Data Labeling Specialists |
|---|---|---|
| Credentials | Typically no formal credentials required; focus on training | Often have training in specific tools or industry standards |
| Work Environment | Collaborative, often remote or in-office teams | Similar, working in teams or independently on labeling tasks |
| Industry Usage | Used by AI/ML companies for training datasets | Employed in similar settings, focusing on labeling data for AI models |
| Search & Comparison Intent | Understanding services offered for data preparation | Looking for roles or tasks related to data labeling |
Data Annotation Services encompass the broader process of preparing and annotating data for AI and machine learning projects, often provided by specialized companies. Data Labeling Specialists are individual professionals or team members who perform the actual labeling tasks within these services. While both are closely related, services refer to the overall offering, whereas specialists are the personnel executing the work.
What are some common challenges faced when working in data annotation services, and how can I address them?
In data annotation services, one common challenge is maintaining consistency and accuracy, especially when handling large datasets or ambiguous data points. Clear annotation guidelines and regular communication with team leads help ensure that everyone interprets the data similarly. Additionally, repetitive tasks can lead to fatigue, so it's important to take scheduled breaks and leverage available annotation tools to streamline workflows. Collaborating with peers to discuss edge cases also helps improve overall data quality and fosters a supportive team environment.
What are data annotation services?
Data annotation services involve labeling or tagging data—such as images, text, audio, or video—to make it understandable for machine learning models. These services are essential in training artificial intelligence systems to recognize patterns, objects, or other relevant information in raw data. Companies use data annotation to improve the accuracy and effectiveness of AI applications, such as self-driving cars, chatbots, and image recognition. Professional annotators or specialized platforms often perform these tasks to ensure high-quality, consistent results.
What job categories do people searching Data Annotation Services jobs in Commack, NY look for? The top searched job categories for Data Annotation Services jobs in Commack, NY are:
What cities near Commack, NY are hiring for Data Annotation Services jobs? Cities near Commack, NY with the most Data Annotation Services job openings:
Full-time
Re-posted 20 days ago
Job description
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: US - NY - Remote
Main duties:
Mandatory Skills
Years of experience: 0-3 Experience working cross-functionally
Job Title: Linguist III
Location: US - NY - Remote
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.
- Must have strong written and spoken communication skills, especially business and research communication.
- Must be near-native proficient in one of the two following languages: German or Turkish and must have a high level of proficiency (CEFRL C1) in the other one of the two previously mentioned languages 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.
- 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.
- 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)
Mandatory Skills
Years of experience: 0-3 Experience working cross-functionally