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Hourly Remote Data Annotation Jobs in Colorado (NOW HIRING)

Alignerr

Machine Learning Engineer

Denver, CO · Remote

$50 - $70/hr

... AI Data Trainer Type : Hourly Contract Compensation : $50-$70 /hour Location : Remote Commitment ... Prior experience with data annotation, data quality, or evaluation systems. * Master's Degree or ...

Alignerr

Computer Engineering

Denver, CO · Remote

$35 - $60/hr

... AI Data Trainer Type : Hourly Contract Compensation : $35-$60 /hour Location : Remote Commitment ... Prior experience with data annotation, data quality, or evaluation systems * Proficiency in ...

Alignerr

Senior Machine Learning Expert

Denver, CO · Remote

$89K - $110K/yr

Hourly Contract * Location : Remote * Commitment : 10-40 hours/week What You'll Do * Author complex ... Prior experience with data annotation, data quality assurance, or AI evaluation pipelines * Top ...

Alignerr

Business Analyst

Denver, CO · Remote

Hourly Contract * Location : Remote * Commitment : 10-40 hours/week What You'll Do * Lead and ... Experience with data annotation, data quality evaluation, or content review workflows * Background ...

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Hourly Remote Data Annotation information

What are the key skills and qualifications needed to thrive as an Hourly Remote Data Annotation Specialist, and why are they important?

To excel as an Hourly Remote Data Annotation Specialist, you need strong attention to detail, accuracy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency with annotation platforms, labeling tools (like Labelbox or Supervisely), and sometimes basic knowledge of spreadsheets or image/video editing software is typically required. Reliability, time management, and clear communication are vital soft skills for succeeding in a remote, deadline-driven environment. These abilities ensure high-quality, consistent annotations that are critical for training AI models and meeting project requirements.

What are some common challenges faced by hourly remote data annotation workers and how can they be addressed?

Hourly remote data annotation workers often encounter challenges such as repetitive tasks, maintaining high accuracy, and managing time effectively without direct supervision. To address these, it's important to establish a structured daily routine, take regular breaks to prevent fatigue, and utilize any quality control guidelines provided by the employer. Staying in regular communication with team leads or project managers can also help clarify any ambiguities and ensure consistent work quality.

What is the difference between Hourly Remote Data Annotation vs Hourly Remote Data Labeling?

AspectHourly Remote Data AnnotationHourly Remote Data Labeling
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageCommon in AI/ML projects for training dataCommon in AI/ML projects for training data
Job FocusAdding annotations to data (e.g., bounding boxes, tags)Assigning labels to datasets for model training

Both roles involve working remotely to prepare data for machine learning models. Data annotation typically involves marking specific features within data, while data labeling involves categorizing data into predefined classes. The skills and work environment are similar, making them closely related but distinct tasks within AI data preparation.

What is hourly remote data annotation?

Hourly remote data annotation involves labeling or categorizing data, such as images, text, or audio, for use in machine learning and artificial intelligence projects. Annotators work from home and are usually paid by the hour to review and tag data according to specific guidelines provided by the employer. This work is essential for training algorithms to recognize patterns or interpret information accurately. Data annotation tasks vary and can include image classification, text categorization, or identifying objects within media. It’s a popular entry-level remote job that requires attention to detail and the ability to follow instructions closely.
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Hourly Remote Data Annotation jobs near you

Software Engineer (C#) - Internal Tooling

Alignerr

Denver, CO • Remote

Other

Posted 7 days ago

Job description

Software Engineer (C#) - Internal Tooling (AI Infrastructure)
About the Role
What if your C# expertise could directly shape the infrastructure powering the next generation of AI? We're looking for experienced full-stack C# engineers to build and improve the systems that leading AI labs depend on - from data annotation pipelines to evaluation harnesses and quality control tooling.
This is a fully remote contract role with flexible commitment. You'll work on real production systems alongside data, research, and engineering teams at the frontier of AI development.
  • Organization
    : Alignerr
  • Type
    : Hourly Contract
  • Location
    : Remote
  • Commitment
    : 20-40 hours/week
What You'll Do
  • Design, build, and optimize high-performance C# systems supporting AI data pipelines and evaluation workflows
  • Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
  • Improve reliability, performance, and safety across existing C# codebases
  • Collaborate with data, research, and engineering teams to support model training and evaluation workflows
  • Identify and resolve bottlenecks and edge cases in data and system behavior with scalable solutions
  • Participate in synchronous design reviews to iterate on architecture and implementation decisions
  • Build and maintain robust benchmarking and performance evaluation harnesses
Who You Are
  • 3-5+ years of professional experience writing production-grade C#
  • Strong full-stack developer background with solid systems programming fundamentals
  • Expertise in interoperability scenarios - such as invoking Python ML models from .NET or wrapping native libraries
  • Experienced designing robust harnesses for benchmarking and evaluating system performance
  • Native or fluent English speaker with clear written and verbal communication skills
  • Able to commit 20-40 hours per week with reliability and consistency
Nice to Have
  • Prior experience with data annotation, data quality, or evaluation systems
  • Familiarity with AI/ML workflows, model training, or benchmarking pipelines
  • Experience with distributed systems or developer tooling
  • Background working with or alongside research teams in a fast-moving environment
Why Join Us
  • Work on cutting-edge AI projects alongside leading research labs
  • Fully remote and flexible - work when and where it suits you
  • Freelance autonomy with the structure of meaningful, high-impact technical work
  • Build systems that directly influence how next-generation AI models are trained and evaluated
  • Potential for ongoing work and contract extension as new projects launch

Apply