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Remote Ai Data Collection Jobs in Portland, OR (NOW HIRING)

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Remote Ai Data Collection information

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$17

$26

$33

How much do remote ai data collection jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for remote ai data collection in Portland, OR is $26.84, according to ZipRecruiter salary data. Most workers in this role earn between $24.71 and $27.55 per hour, depending on experience, location, and employer.

What is remote AI data collection?

Remote AI data collection refers to the process of gathering and labeling data—such as images, audio, text, or video—from various sources using digital tools, often from a remote location. This data is used to train and improve artificial intelligence and machine learning models. People working in this field can perform tasks like annotating images, transcribing audio, or categorizing text, all from their home or another remote setting. The work is essential for creating accurate AI systems and often offers flexible hours. It usually requires basic computer skills and attention to detail.

What skills and qualifications are needed for a remote AI data collection specialist?

To thrive as a Remote AI Data Collection Specialist, you need attention to detail, data management skills, and a basic understanding of machine learning concepts, often supported by a degree in computer science or related fields. Familiarity with data annotation tools, spreadsheets, and platforms like Labelbox or Amazon SageMaker is commonly required. Strong communication, time management, and problem-solving skills are important for collaborating remotely and meeting project deadlines. These abilities ensure accurate, efficient data gathering and annotation, which are critical for the quality and reliability of AI model development.

What are common challenges in a remote AI data collection role, and how can they be managed?

A common challenge in Remote AI Data Collection roles is ensuring data quality and consistency, especially when working independently without direct supervision. It is important to follow detailed guidelines precisely and communicate proactively with project managers or team leads whenever uncertainties arise. Time management and maintaining motivation can also be challenging when working remotely, so setting a structured schedule and leveraging collaboration tools can help. Regular check-ins with the team and staying updated with project requirements are key to overcoming these challenges and delivering reliable results.

What is the difference between Remote Ai Data Collection vs Remote Data Annotator?

AspectRemote Ai Data CollectionRemote Data Annotator
Required CredentialsBasic computer skills, training in data collection toolsAttention to detail, familiarity with annotation software
Work EnvironmentRemote, flexible hours, often on mobile or desktopRemote, flexible hours, often on desktop or specialized platforms
Industry UsageAI training data gathering across various sectorsLabeling and annotating data for machine learning models
Common Search IntentJobs involving data collection for AIJobs focused on data labeling and annotation

Remote Ai Data Collection involves gathering raw data for AI training, often requiring basic technical skills. Remote Data Annotator focuses on labeling and annotating data to improve machine learning models. Both roles are remote, but they differ in tasks and skill requirements, serving different stages of AI data preparation.

What are the most commonly searched types of Ai Data Collection jobs in Portland, OR?

The most popular types of Ai Data Collection jobs in Portland, OR are:

What are popular job titles related to Remote Ai Data Collection jobs in Portland, OR?

For Remote Ai Data Collection jobs in Portland, OR, the most frequently searched job titles are:

What cities near Portland, OR are hiring for Remote Ai Data Collection jobs?

Cities near Portland, OR with the most Remote Ai Data Collection job openings:

Infographic showing various Remote Ai Data Collection job openings in Portland, OR as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $55,825 per year, or $26.8 per hour.

Computational Biologist - AI Reviewer

micro1 AI

Beaverton, OR • On-site, Remote

$90 - $120/hr

Part-time

Posted 23 days ago


Job description

Role Title: Computational Biology Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology Experts to contribute their advanced scientific knowledge to a dynamic 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.


Scope of Work

  1. Analyze and annotate complex biological data sets, focusing on applications relevant to medicinal chemistry.
  2. Provide feedback and domain-specific insights to improve AI models in computational biology contexts.
  3. Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with industry standards.
  4. Develop and review problem sets, case studies, or scenarios based on real-world medicinal chemistry challenges.
  5. Collaborate asynchronously with other experts to validate findings and share perspectives on project deliverables.
  6. Contribute to the refinement of data curation methodologies and best practices in computational biology.


Preferred Qualifications

  1. Advanced degree (PhD, PharmD, or MSc) in computational biology, medicinal chemistry, bioinformatics, or a closely related field.
  2. Demonstrated expertise in medicinal chemistry, including experience with drug discovery or design.
  3. Strong analytical skills with a deep understanding of biological datasets and scientific literature.
  4. Experience applying computational methods to solve problems in chemistry or biology.
  5. Proficiency with relevant bioinformatics tools, cheminformatics platforms, or data analysis software.
  6. Excellent written communication skills to clearly explain complex scientific concepts to diverse audiences.
  7. Previous participation in cross-disciplinary or AI-driven scientific projects is a plus.