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Remote Data Annotation Analyst Jobs (NOW HIRING)

Innodata Inc.

$15.75 - $21.25/hr

Innodata Inc. is seeking Freelance Data Annotation Specialists to support global AI and Large Language Model (LLM) projects. This project-based opportunity is ideal for individuals seeking ...

DataAnnotation

$40/hr

A remote data annotation company is seeking a Microbiologist to train AI models by evaluating their outputs and improving their quality. The position offers flexibility in choosing projects and ...

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Remote Data Annotation Analyst information

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$34K

$82.6K

$136K

How much do remote data annotation analyst jobs pay per year?

As of Jun 3, 2026, the average yearly pay for remote data annotation analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Data Annotation Analyst, and why are they important?

To thrive as a Remote Data Annotation Analyst, you need strong attention to detail, analytical thinking, and a high school diploma or equivalent, with many roles preferring experience in data-related tasks. Familiarity with data annotation platforms (like Labelbox or AWS SageMaker Ground Truth) and basic understanding of data management tools are typically required. Excellent time management, self-motivation, and clear communication help analysts manage remote workloads and collaborate effectively with distributed teams. These skills ensure accurate, high-quality annotated data essential for training and validating machine learning models.

How does a Remote Data Annotation Analyst typically collaborate with team members and ensure consistent labeling standards?

As a Remote Data Annotation Analyst, you’ll frequently work within a distributed team, using collaboration tools such as Slack, project management platforms, and shared annotation guidelines. Regular virtual meetings and feedback sessions help ensure everyone applies labeling standards consistently and resolves ambiguities. It’s common to review peer annotations and participate in quality assurance checks, promoting a culture of accuracy and continuous improvement. Clear communication and attention to detail are essential for maintaining high-quality annotated datasets across the team.

What are Remote Data Annotation Analysts?

Remote Data Annotation Analysts are professionals who label, categorize, or tag data—such as images, text, audio, or video—from a remote location. Their work helps train machine learning algorithms by providing structured datasets that computers can learn from. These analysts use specialized tools to identify relevant features in raw data, ensuring accuracy and consistency. The role often requires attention to detail, basic technical skills, and the ability to follow specific guidelines or instructions. This position is commonly found in industries like artificial intelligence, autonomous vehicles, and natural language processing.

What is the difference between Remote Data Annotation Analyst vs Remote Data Labeler?

AspectRemote Data Annotation AnalystRemote Data Labeler
Required CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentHome-based, flexible hoursHome-based, flexible hours
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnalyzing and verifying labeled data, quality controlLabeling data, annotating images, text, or audio

The main difference is that Remote Data Annotation Analysts focus on verifying and ensuring the quality of labeled data, often involving analysis and review, while Remote Data Labelers primarily perform the task of labeling or annotating raw data. Both roles are essential in AI development and share similar work environments and skill requirements, but their specific responsibilities differ in scope and focus.

More about Remote Data Annotation Analyst jobs
What cities are hiring for Remote Data Annotation Analyst jobs? Cities with the most Remote Data Annotation Analyst job openings:
What are the most commonly searched types of Data Annotation Analyst jobs? The most popular types of Data Annotation Analyst jobs are:
What states have the most Remote Data Annotation Analyst jobs? States with the most job openings for Remote Data Annotation Analyst jobs include:
What job categories do people searching Remote Data Annotation Analyst jobs look for? The top searched job categories for Remote Data Annotation Analyst jobs are:
Remote Data Annotation Analyst jobs near you
Infographic showing various Remote Data Annotation Analyst job openings in the United States as of May 2026, with employment types broken down into 100% Part Time. Highlights an 46% Physical, 1% Hybrid, and 53% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Backend Developer - Data Annotation Systems

Alignerr

Denver, CO • Remote

Other

This job post has expired today. Applications are no longer accepted.

Job description

Backend Developer - Data Annotation Systems (AI Infrastructure)
About the Role
What if your Python expertise could directly shape the infrastructure behind the world's most advanced AI models? We're looking for a Senior Python Full-Stack Engineer to design and build the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and improve next-generation models.
This is a fully remote, flexible contract role for an experienced engineer who wants to work on real production systems at the cutting edge of AI development - not toy projects, but infrastructure that matters.
  • Organization
    : Alignerr
  • Type
    : Hourly Contract
  • Location
    : Remote
  • Commitment
    : 20-40 hours/week
What You'll Do
  • Design, build, and optimize high-performance Python systems that support large-scale AI data pipelines and evaluation workflows
  • Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale
  • Improve the reliability, performance, and safety of existing Python codebases
  • Collaborate with data, research, and engineering teams to support model training and evaluation infrastructure
  • Identify bottlenecks and edge cases in data and system behavior - then implement scalable, production-ready fixes
  • Participate in synchronous design reviews to iterate on architecture and implementation decisions
Who You Are
  • Native or fluent English speaker with clear written and verbal communication skills
  • Full-stack developer with a strong systems programming background
  • 3-5+ years of professional experience writing production-grade Python
  • Experienced building asynchronous task queues for long-running background jobs
  • Proficient in optimizing database queries for high-read/write workloads and serving data via real-time protocols (e.g., WebSockets)
  • Able to commit 20-40 hours per week with reliability and consistency
Nice to Have
  • Prior experience with data annotation, data quality pipelines, or evaluation systems
  • Familiarity with AI/ML workflows, model training, or benchmarking infrastructure
  • Experience with distributed systems or internal developer tooling
Why Join Us
  • Work directly with leading AI research labs on production-grade, high-impact systems
  • Fully remote and flexible - work from anywhere on a schedule that suits you
  • Freelance autonomy with the structure and focus of meaningful, substantive engineering work
  • Make a direct, tangible contribution to the infrastructure shaping the future of AI
  • Potential for ongoing work and contract extension as new projects launch

Apply