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Ai Llm Data Labeling Jobs (NOW HIRING)

Aerotek

Data Labeling Specialist

San Jose, CA

$30/hr

Data Labeling Specialist We are seeking a detail-oriented Data Labeling Specialist to join our ... Join a first-of-its-kind AI robotics company focused on bringing a general-purpose humanoid to life.

TMS

AI/ LLM Engineer- Next.js

Princeton, NJ · On-site

Key Requirements AI / LLM Integration (Must Have) * Hands-on experience integrating OpenAI, Azure ... Strong understanding of NoSQL data modeling and scalability patterns. Next.js (Must Have) * Proven ...

Public Storage

Generative AI/LLM Engineer

Frisco, TX · On-site

We are seeking a Generative AI / LLM Engineer with strong full-stack and Python development ... Build APIs, microservices, and interfaces to deliver AI solutions end-to-end, from data ingestion ...

Public Storage

Generative AI/LLM Engineer

Frisco, TX · On-site

We are seeking a Generative AI / LLM Engineer with strong full-stack and Python development ... Build APIs, microservices, and interfaces to deliver AI solutions end-to-end, from data ingestion ...

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Ai Llm Data Labeling information

What is AI LLM data labeling?

AI LLM data labeling is the process of annotating or tagging data—such as text, images, or audio—to provide clear examples that help train large language models (LLMs) like GPT or BERT. This labeled data is essential for teaching models to understand context, intent, and meaning, which improves their performance on various tasks. Data labelers often follow specific guidelines to ensure consistency and accuracy, making their role critical in developing reliable AI systems.

What is the difference between Ai Llm Data Labeling vs Data Annotation Specialist?

AspectAi Llm Data LabelingData Annotation Specialist
CredentialsBasic technical skills, familiarity with labeling toolsSimilar technical skills, often with additional domain knowledge
Work EnvironmentData labeling platforms, remote or office settingsData annotation projects, remote or onsite
Industry UsageAI, machine learning, NLP projectsData preparation across various industries including AI

Ai Llm Data Labeling and Data Annotation Specialist roles both involve preparing data for machine learning models. However, Ai Llm Data Labeling typically focuses on labeling data specifically for large language models, requiring familiarity with NLP and AI tools. Data Annotation Specialists may work across broader data types and industries, with a focus on accurate data tagging. Both roles demand similar skills but differ in scope and application within AI projects.

What are the key skills and qualifications needed to thrive as an AI LLM data labeling specialist, and why are they important?

To thrive as an AI LLM Data Labeling Specialist, you need keen attention to detail, strong analytical skills, and a foundational understanding of natural language processing concepts, often supported by familiarity with data annotation guidelines. Experience with labeling platforms (such as Labelbox or Prodigy), spreadsheet tools, and sometimes proficiency in scripting languages like Python is highly valued. Excellent communication, consistency, and critical thinking are crucial soft skills for interpreting ambiguous data and ensuring labeling accuracy. These skills and qualifications are vital for producing high-quality training data that directly impacts the performance and reliability of large language models.

What are some common challenges faced in AI LLM data labeling and how can they be managed?

One common challenge in AI LLM data labeling is ensuring consistency and accuracy when annotating large volumes of complex language data. Labelers often encounter ambiguous or context-dependent text, making it important to follow detailed guidelines and participate in regular calibration sessions with the team. Collaboration with data scientists and project managers is essential to clarify edge cases and refine labeling criteria. Proactively communicating questions and feedback helps maintain high-quality datasets, which are critical for training reliable language models.
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Infographic showing various Ai Llm Data Labeling job openings in the United States as of August 2026, with employment types broken down into 75% Full Time, and 25% Contract. Highlights an 100% In-person job distribution.

Ophthalmologist (Medical Data Labeling Specialist)

Saviance

Boston, MA • On-site

Other

Re-posted 15 days ago

Job description

Ophthalmologist (Medical Data Labeling Specialist)
Location: India, Remote
Duration: Ongoing Part-Time
About BigRio
BigRio is a Boston-based, remote-first technology consulting firm specializing in advanced data and software solutions. We partner with forward-thinking organizations to deliver scalable, cost-effective, and innovative technology, with particular expertise in AI/ML, data engineering, and cloud-native applications. Our clients span healthcare, life sciences, government, and enterprise sectors, and we are known for our ability to tackle complex challenges with cutting-edge solutions.
About Job:
This role leverages the clinical expertise of an ophthalmologist to accurately annotate and label medical data, primarily images and structured clinical data related to eye health, for the development and refinement of artificial intelligence (AI) and machine learning (ML) models in ophthalmology.
Responsibilities
Key responsibilities include:
  • Data Annotation: Reviewing and annotating various ophthalmic data like fundus images, Optical Coherence Tomography (OCT) scans, and other visual data, identifying anatomical structures and disease markers.
  • Adherence to Protocols: Applying standardized grading protocols consistently for accurate and consistent labeling.
  • Quality Control & Feedback: Participating in calibration sessions and reviews to maintain annotation consistency.
  • Collaboration: Working with AI engineers and data scientists to ensure the clinical validity of guidelines.
  • AI Model Validation: Validating AI model outputs for clinical accuracy and safety.
  • Patient Education Material Development (potential): Possibly creating or reviewing materials for AI/ML algorithms to provide accurate patient education.
  • Privacy and Security: Ensuring compliance with patient privacy and data security policies, like HIPAA.
Qualifications
Essential qualifications typically include:
  • Ophthalmologist (MBBS) with at least 1-2 years of clinical experience.
  • Extensive Clinical Knowledge: In-depth understanding of various eye conditions.
  • Experience in Clinical Data Review: Familiarity with medical record documentation.
  • Attention to Detail: Commitment to accurate annotation.
  • Communication Skills: Excellent communication skills, both written and verbal, in English.
  • Teamwork: Ability to collaborate effectively with a multidisciplinary team.
Required skills often include:
  • Medical Image Annotation: Proficiency in using annotation tools to delineate structures and pathologies
  • Data Interpretation and Assessment: Skill in interpreting data related to medical products and AI model performance.
  • Problem Solving: Ability to identify challenges and recommend solutions.
  • Adaptability: Ability to adapt to varying image resolutions and file formats.

This role offers a unique opportunity to contribute to the development of AI tools that can improve eye health and patient care on a wider scale.
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About Saviance

Sourced by ZipRecruiter

Saviance is a modern consulting firm providing a variety of professional services to its clients in the US. We bring twenty three years of experience to the table. Our consultants are qualified experts and extremely talented. We understand the business behind the technology, and work with many of the top Fortune 100 companies and provide innovative, scalable, robust and secure solutions. At the forefront of the Staffing and IT Solutions industry, Saviance is certified by NMSDC as a Tier 1, Minority Business Enterprise (MBE) . We are a self- certified Small Business and self- certified Woman Owned Business committed to maximizing global workforce solutions on behalf of our clients, empowering businesses and talent through applied human intelligence. We are a Diversity Supplier with global reach specializing in a business services blend of talent, technology, and a relentless commitment to customer success. It’s our diversity that’s acts as a core component of our culture, our approach to business, and the opportunities we provide to our clients and our employees.

Industry

It services

Company size

201 - 500 Employees

Headquarters location

East Rutherford, NJ, US

Year founded

1999

Social media

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