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Contractual Remote Data Annotation Jobs in Colorado

Alignerr

Machine Learning Engineer

Denver, CO · Remote

$50 - $70/hr

Prior experience with data annotation, data quality, or evaluation systems. * Master's Degree or PhD Why Join Us: * Competitive pay and flexible remote work. * Collaborate with a team working on ...

Alignerr

Computer Engineering

Denver, CO · Remote

$35 - $60/hr

Computer Engineering - AI Data Trainer * Location: Remote About the job At Alignerr, we partner ... Prior experience with data annotation, data quality, or evaluation systems * Proficiency in ...

Alignerr

Senior Machine Learning Expert

Denver, CO · Remote

$89K - $110K/yr

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

Alignerr

Business Analyst

Denver, CO · Remote

Experience with data annotation, data quality evaluation, or content review workflows * Background ... Fully remote and flexible - work when and where it suits you * Freelance autonomy with the ...

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All JobsContractual Remote Data Annotation JobsContractual Remote Data Annotation Jobs in Colorado

Contractual Remote Data Annotation information

What is contractual remote data annotation?

Contractual remote data annotation involves labeling or tagging data—such as images, text, or audio—while working from a remote location, usually as a contractor rather than a full-time employee. Data annotation is a crucial step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms learn to recognize patterns and make predictions. Contractors are typically assigned specific tasks or projects and are paid based on the volume or quality of their completed annotations. This type of work requires attention to detail, reliability, and sometimes domain-specific knowledge, depending on the project.

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

AspectContractual Remote Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote or on-site, flexible or fixed hours
Industry UsageAI, machine learning, tech companiesAI, machine learning, tech companies
Job ScopeAnnotating data for training AI modelsLabeling data to train AI systems

Contractual Remote Data Annotation involves completing data annotation tasks on a contractual basis, often with flexible hours and remote work. Data Labelers perform similar tasks but may work on a freelance or part-time basis, sometimes in different environments. Both roles support AI development, but Contractual Remote Data Annotation typically emphasizes contractual agreements and remote flexibility.

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

To thrive as a Contractual Remote Data Annotation Specialist, you need strong attention to detail, familiarity with data labeling concepts, and often a basic understanding of machine learning or AI workflows. Proficiency with annotation platforms like Labelbox, Supervisely, or Amazon SageMaker Ground Truth, as well as experience with common data types such as images, text, or audio, is typically required. Reliability, time management, and clear communication are essential soft skills for meeting deadlines and maintaining quality in remote, independent work. These skills and qualifications ensure accuracy and efficiency, which are critical for producing high-quality datasets that power AI and machine learning models.

What are some common challenges faced by contractual remote data annotators, and how can they be addressed?

Contractual remote data annotators often face challenges such as repetitive tasks, maintaining accuracy over long periods, and managing communication with distributed teams. To address these, it's important to establish a structured workflow, take regular breaks to prevent fatigue, and use quality control tools provided by employers. Staying proactive in seeking clarification on annotation guidelines and participating in team discussions can also help ensure consistent results and foster a supportive remote work environment.
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Contractual 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