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Temporary Ai Data Annotation Jobs in Colorado (NOW HIRING)

Garmin Ltd.

Data Scientist 1

Louisville, CO · On-site

$85 - $115/hr

... AI products. This role will also leverage machine learning, statistical analysis, and data ... Build and deploy annotation, training, and evaluation pipelines and automate workflows to improve ...

Sierra Space Corporation

Computer Vision II

Centennial, CO · On-site

$105K - $145K/yr

You will design and develop sophisticated AI software and hardware for satellite applications ... Experience with data annotation and management for training computer vision models. * Knowledge of ...

Sierra Space Corporation

Computer Vision II

Centennial, CO · On-site

$105K - $145K/yr

You will design and develop sophisticated AI software and hardware for satellite applications ... Experience with data annotation and management for training computer vision models. * Knowledge of ...

Acara Solutions

Data Technician III

Littleton, CO

$26/hr

Temporary, 12+ months Industry: Aerospace and Defense Compensation: $26/hr Schedule: 9x80 About the ... AI agent role is to help speed up your hiring process by answering questions, confirming basic ...

Aleron

Data Technician III

Littleton, CO · On-site

$26/hr

Temporary, 12+ months Industry: Aerospace and Defense Compensation: $26/hr Schedule: 9x80 About the ... AI agent role is to help speed up your hiring process by answering questions, confirming basic ...

New

Judge Group, Inc.

Principal AI/ML Engineer

Englewood, CO · On-site

$75 - $80.15/hr

Englewood, CO Duration: 6 Months Temp to Hire Pay: $80.15/hr. on W2 Job Summary We are seeking a ... Data management and governance * Model development and versioning * CI/CD for machine learning

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Temporary Ai Data Annotation information

What is a temporary AI data annotation job?

Temporary AI Data Annotation jobs involve labeling, categorizing, or tagging data such as images, text, audio, or video for the purpose of training artificial intelligence (AI) and machine learning models. These roles are often short-term or contract positions, as they are needed for specific projects or during certain stages of data processing. Annotators play a critical role in ensuring the quality and accuracy of datasets, which directly impacts the performance of AI systems. No advanced technical skills are usually required, but attention to detail and consistency are important. These jobs may be offered remotely or on-site, depending on the employer.

What is the difference between Temporary Ai Data Annotation vs Data Labeler?

AspectTemporary Ai Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic skills, sometimes specific software knowledge
Work EnvironmentRemote or on-site, project-basedRemote or on-site, often similar settings
Industry UsageAI, machine learning, tech companiesAI, autonomous vehicles, tech sectors
Job FocusAnnotating data for AI trainingLabeling data for machine learning models

Temporary Ai Data Annotation involves short-term projects focused on preparing data for AI systems, while Data Labeler is a broader role that includes labeling various data types for machine learning. Both roles require similar skills and are used in tech industries, but Temporary Ai Data Annotation emphasizes project-based work specifically for AI training datasets.

What are the key skills and qualifications needed to thrive as a temporary AI data annotation specialist, and why are they important?

To thrive as a Temporary AI Data Annotation Specialist, you need keen attention to detail, strong analytical skills, and the ability to follow complex guidelines, often supported by a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools like Labelbox or Prodigy, and basic computer literacy are typically required. Reliability, consistency, and the ability to work independently stand out as valuable soft skills in this role. These competencies are essential for producing high-quality, accurate data that directly impacts the effectiveness of machine learning models.

What are some common challenges faced in a temporary AI data annotation role, and how can they be managed?

One of the main challenges in a Temporary AI Data Annotation position is maintaining consistent accuracy and attention to detail, especially when working with large volumes of data. Annotation guidelines can be complex and may change depending on project requirements, so adaptability and clear communication with the team are key. Managing repetitive tasks while ensuring high-quality work can be demanding, but using productivity tools and taking regular breaks can help maintain focus. Collaborating with quality assurance leads and participating in feedback sessions are also important for continuous improvement.
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Temporary Ai Data Annotation jobs near you

Medical Microbiology Consultant - Remote

micro1 AI

Denver, CO • Remote

$70 - $90/hr

Part-time

Posted 13 days ago

Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelor’s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Master’s or PhD) in a relevant field.

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