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Remote Arabic Ai Training information

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$77

How much do remote arabic ai training jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for remote arabic ai training in the United States is $42.21, according to ZipRecruiter salary data. Most workers in this role earn between $27.88 and $53.85 per hour, depending on experience, location, and employer.

What is the difference between Remote Arabic Ai Training vs Remote Arabic Content Annotator?

AspectRemote Arabic Ai TrainingRemote Arabic Content Annotator
Required CredentialsBasic understanding of AI, language proficiency, sometimes certifications in AI or linguisticsLanguage proficiency, attention to detail, sometimes basic technical skills
Work EnvironmentRemote, collaborative with AI development teamsRemote, focused on data labeling and annotation tasks
Employer & Industry UsageAI companies, tech startups, language technology firmsData annotation companies, AI training datasets providers

Remote Arabic Ai Training involves preparing AI models through tasks like data collection and model tuning, requiring some technical knowledge. In contrast, Remote Arabic Content Annotator focuses on labeling and annotating data to improve AI accuracy, emphasizing attention to detail. Both roles are remote and essential for AI development, but they differ in technical complexity and specific responsibilities.

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Remote Arabic Ai Training jobs near you
Infographic showing various Remote Arabic Ai Training job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $87,800 per year, or $42.2 per hour.

AI Training Specialist - Cheminformatics

micro1 AI

Brownsville, TX • Remote

$80 - $110/hr

Part-time

Posted 11 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.

Apply