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Ai Task Reviewer Jobs in Raleigh, NC (NOW HIRING)

Review and interpret scientific literature to provide contextually accurate and current insights ... Apply sophisticated calculus and quantitative methodologies to problem-solving tasks * Ensure ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... AI performance on contract tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions.

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Ai Task Reviewer information

See Raleigh, NC salary details

$10

$29

$47

How much do ai task reviewer jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for ai task reviewer in Raleigh, NC is $29.05, according to ZipRecruiter salary data. Most workers in this role earn between $21.97 and $35.53 per hour, depending on experience, location, and employer.

How to become an AI task reviewer?

To become an AI task reviewer, candidates typically need strong attention to detail, good understanding of AI and machine learning concepts, and experience with data annotation or content moderation. Relevant skills include familiarity with review tools and platforms, and some roles may require a background in linguistics, computer science, or related fields. Gaining experience through online courses or certifications can also improve prospects in this role.

Are remote AI task reviewer jobs legit?

Remote AI task reviewer jobs are legitimate positions where individuals evaluate and annotate data to improve AI systems. These roles often require attention to detail, basic computer skills, and sometimes specific training or guidelines, and they are commonly offered by reputable companies in the tech industry.

What is the difference between Ai Task Reviewer vs Data Annotator?

AspectAi Task ReviewerData Annotator
Required CredentialsBasic computer skills, training in review guidelinesBasic computer skills, training in annotation tools
Work EnvironmentRemote or office-based, reviewing AI outputsRemote or office-based, labeling and annotating data
Industry UsageAI development, machine learning projectsData preparation, machine learning datasets
Search & Comparison IntentUnderstanding review roles in AI projectsUnderstanding data labeling roles in AI

The main difference between an Ai Task Reviewer and a Data Annotator lies in their roles within AI development. Ai Task Reviewers focus on evaluating and validating AI outputs, ensuring quality and accuracy, while Data Annotators are responsible for labeling and preparing data used to train AI models. Both roles are essential in the AI industry, often requiring similar skills but serving different functions in the data pipeline.

What are popular job titles related to Ai Task Reviewer jobs in Raleigh, NC? For Ai Task Reviewer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Ai Task Reviewer jobs in Raleigh, NC look for? The top searched job categories for Ai Task Reviewer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Ai Task Reviewer jobs? Cities near Raleigh, NC with the most Ai Task Reviewer job openings:
Infographic showing various Ai Task Reviewer job openings in Raleigh, NC as of August 2026, with employment types broken down into 82% Full Time, 11% Part Time, and 7% Contract. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $60,424 per year, or $29.1 per hour.

Bioinformatics Research Scientist - AI Reviewer

micro1 AI

Durham, NC • Remote

$80 - $110/hr

Part-time

Posted 9 days ago


Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery 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 interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.