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Llm Annotation Jobs (NOW HIRING)

Arrive Logistics

Data Scientist II

Chicago, IL · On-site

Develop, evaluate, and iterate on NLP and LLM-based systems, including text classification ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Arrive Logistics

Data Scientist II

Austin, TX · On-site

Develop, evaluate, and iterate on NLP and LLM-based systems, including text classification ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Arrive Logistics

Data Scientist II

Chicago, IL · On-site +1

$130K - $150K/yr

Develop, evaluate, and iterate on NLP and LLM-based systems, including text classification ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Arrive Logistics

Data Scientist II

Austin, TX · On-site +1

Develop, evaluate, and iterate on NLP and LLM-based systems, including text classification ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Mill

AI Engineer, Computer Vision

San Bruno, CA

Experience with foundation models for data annotation * Experience with MLOps tooling (Weights & Biases, MLflow, SageMaker, or equivalents) * Experience shipping LLM- or agent-powered features in a ...

Nastech Global

GEN AI Engineer

Charlotte, NC · On-site

Roles & Responsibilities o Implement Guardrails and observability across RAG and LLM applications o ... Implement annotation,structured feedback loops,fine-tuning, and alignment methods to calibrate ...

Mill

AI Engineer, Computer Vision

San Bruno, CA · On-site

Experience with foundation models for data annotation * Experience with MLOps tooling (Weights & Biases, MLflow, SageMaker, or equivalents) * Experience shipping LLM- or agent-powered features in a ...

Waymo

Software Engineer, Labeling Infrastructure

$177K - $209K/yr

Preferred : • Experience in developing diverse data annotation tooling and infrastructure. • ... LLM/GenAI-based products. Company : Waymo is a mobility technology company that improves ...

CreatorIQ, Inc

ML Engineer

Los Angeles, CA · On-site

$132K - $165K/yr

Partner with Data Science on annotation workflows, PII scrubbing, and ground-truth pipelines ... Practical experience with evaluation for ML or LLM systems - golden datasets, model-as-a-judge, IAA ...

Welocalize, Inc.

Data Labeling Associate

New York, NY · On-site

$17.50 - $22.75/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation ...

Welocalize, Inc.

Data Labeling Associate

San Diego, CA

$17 - $22/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation ...

Welocalize, Inc.

Data Labeling Analyst

San Diego, CA · On-site

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation ...

Welocalize, Inc.

Data Labeling Associate

New York, NY

$17.50 - $22.75/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Deliver detailed reports on findings, including aspects such as utterance quality, LLM evaluation ...

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Llm Annotation information

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$11K

$41.5K

How much do llm annotation jobs pay per year?

As of Jul 12, 2026, the average yearly pay for llm annotation in the United States is $40,000.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,000.00 and $40,000.00 per year, depending on experience, location, and employer.

Which 5 jobs will survive AI?

Jobs involving LLM annotation, such as data annotators and labelers, are likely to persist as they require human judgment for complex or nuanced tasks. Roles that involve creative thinking, emotional intelligence, and strategic decision-making, like psychologists, teachers, healthcare professionals, and managers, are also expected to remain in demand despite AI advancements. These jobs often require skills that are difficult for AI to replicate fully.

How much do AI annotators make?

AI annotators, including those working as language model annotation specialists, typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the tasks. Some positions may offer hourly wages or project-based pay, with higher rates for specialized skills or advanced tools proficiency.

Are data annotations still hiring?

Data annotation roles, including those for large language models (LLMs), are currently in demand as companies continue to develop AI and machine learning systems. These jobs often require attention to detail and familiarity with annotation tools, and opportunities are available through various online platforms and companies expanding their AI teams.

What is an LLM annotator?

An LLM annotator is a person who labels and tags data to train large language models (LLMs). They review and annotate text data to improve model accuracy, often using specialized tools and following specific guidelines. This role requires attention to detail and understanding of language patterns.

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.

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, and why are they important?

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.
More about Llm Annotation jobs
What cities are hiring for Llm Annotation jobs? Cities with the most Llm Annotation job openings:
What states have the most Llm Annotation jobs? States with the most job openings for Llm Annotation jobs include:
What job categories do people searching Llm Annotation jobs look for? The top searched job categories for Llm Annotation jobs are:
Llm Annotation jobs near you
Infographic showing various Llm Annotation job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 34% Full Time, 31% Part Time, and 34% Contract. Highlights an 34% Physical, and 66% Remote job distribution, with an average salary of $40,000 per year, or $19.2 per hour.
Data Scientist II

Data Scientist II

Arrive Logistics

Chicago, IL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 20 days ago

Arrive Logistics rating

4.3

Company rating: 4.3 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

Job description

Who We Are
Arrive Logistics is a leading transportation and technology company in North America with plans to grow significantly year over year. Our success is a testament to our remarkable team and what we're building together. We're committed to providing employees with a meaningful work experience and have established an award-winning culture that supports personal and career development in a fun, casual, and collaborative environment.
Who We Want
The Data Scientist II will work closely with Data Science, Product, and Engineering to build and improve ML and AI systems that drive operational value. This role is a great fit for a hands-on practitioner with applied experience in NLP and LLM-based systems who is ready to take on meaningful technical ownership. You'll contribute to the full lifecycle of production ML systems - from evaluation and measurement through development, deployment, and iteration - with a particular focus on text and language-based applications. The ideal candidate is comfortable operating in ambiguous problem spaces, can translate loosely defined business needs into concrete technical approaches, and communicates findings clearly to both technical and non-technical audiences.
What You'll Do
  • Develop, evaluate, and iterate on NLP and LLM-based systems, including text classification, information extraction, and context retrieval pipelines.
  • Build measurement and evaluation frameworks - both offline and online - to assess where and why systems are underperforming and quantify the impact of improvements.
  • Develop golden test datasets and define methodologies for creating and maintaining them over time, including designing annotation guidelines and ensuring label quality.
  • Evaluate and apply the appropriate approach for language tasks - whether prompt engineering, fine-tuning, or classical NLP methods - including modern retrieval and RAG architectures and LLM evaluation methodologies, based on the problem and available data.
  • Perform structured analysis of system performance to surface failure modes, data gaps, and high-value areas for investment, applying sound statistical reasoning to evaluation results.
  • Partner with engineers to support deployment, integration, and monitoring of ML and AI systems in production.
  • Contribute to standards and best practices around deploying, evaluating, and monitoring text and language-based ML systems.
  • Document work clearly and maintain knowledge artifacts that make systems understandable and maintainable over time.
  • Collaborate with senior data scientists and cross-functional partners to translate business needs into well-scoped technical solutions, including communicating findings and recommendations to non-technical stakeholders.

Qualifications
  • Bachelor's or Master's degree in a quantitative field (computer science, statistics, linguistics, or related) and 2-4 years of applied ML or data science experience, or equivalent practical experience.
  • Hands-on experience building or improving NLP or LLM-based systems in applied settings.
  • Familiarity with text classification, information extraction, or other NLP tasks - and an understanding of where these systems fail.
  • Experience with both prompt engineering and fine-tuning approaches for language tasks, with the judgment to know when to apply each.
  • Familiarity with modern retrieval strategies and RAG architectures and how they affect LLM system performance.
  • Experience with Hugging Face Transformers for text classification or related NLP tasks.
  • Experience contributing to evaluation frameworks, test sets, or performance diagnostics for ML systems, including comfort with statistical methods for measuring model performance.
  • Proficiency in Python and SQL, and comfort working with structured and unstructured data.
  • Ability to operate effectively in ambiguous problem spaces - scoping technical approaches when requirements are not fully defined.
  • Strong written communication skills; able to document systems and findings clearly and present recommendations to non-technical stakeholders.
  • Experience designing data annotation workflows, labeling guidelines, or label quality processes is a plus.
  • Experience with model deployment, monitoring, or production ML workflows is a plus.
  • Familiarity with LangChain and LangSmith or similar LLM orchestration and observability tooling is a plus.
  • Transportation or logistics industry experience is a plus.

The Perks of Working With Us
  • Take advantage of our comprehensive benefits package, including medical, dental, vision, life, disability, and supplemental coverage.
  • Invest in your future with our matching 401(k) program.
  • Build relationships and take part in learning opportunities through our Employee Resource Groups.
  • Enjoy office wide engagement activities, team events, happy hours and more!
  • Leave the suit and tie at home; our dress code is casual.
  • Work in the heart of downtown Chicago, IL!
  • Sweat it out at the LifeStart gym in our office building that includes brand new Peloton bikes, top-of-the-line equipment and personal training options.
  • Maximize your wellness with free counseling sessions through our Employee Assistance Program
  • Take time to manage your physical and mental health - we offer company paid holidays, paid vacation time and wellness days.
  • Receive 100% paid parental leave when you become a new parent.
  • Get paid to work with your friends through our Referral Program!
  • Get relocation assistance! If you are not local to the area, we offer relocation packages.

$130,000 - $150,000 a year
The base salary range for this position is $130K - $150K, plus bonus and benefits. The range displayed on each job posting reflects the pay range for the position across all locations. Within the range, individual pay is determined based on work location, job-related skills, experience, relevant education or training.
Your Arrive Experience
When we say "award-winning culture," we mean it. We've been recognized as a top workplace by Inc. Fast Company, Fortune, and earned Top Workplaces and Great Place to Work, to name a few. We intend on topping many more of those lists in the years to come, but we're not in it for the trophies. We're committed to culture because it keeps us connected to each other and invested in our shared success while having a blast along the way. Our employee-founded resource groups create communities within Arrive's walls, including Women in Logistics, Emerging Professionals, Prisms, Black Logistics Group, Salute and Unidos.
Notice:
To ensure a safe and transparent interview process, we want to note that Arrive Logistics adheres to strict recruitment practices. Candidates undergo an interview process, and Arrive Logistics does not provide unsolicited job offers. If you have concerns about receiving a fraudulent offer, please contact [email protected] for verification.

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