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Ai Tester Jobs in Raleigh, NC (NOW HIRING)

We are seeking an AI Developer to design and build AIpowered solutions using Microsoft's AI ... Build CI/CD pipelines that support automated testing, security scanning, and deployments to Azure.

Lead AI Quality Assurance Engineer

Raleigh, NC ยท Hybrid

$125K/yr

Leads testing efforts for moderately complex AI products, features and platform enhancements. * Designs advanced test plans covering model accuracy, bias detection, explainability and operational ...

Lead AI Quality Assurance Engineer

Raleigh, NC ยท Hybrid

$125K/yr

Leads testing efforts for moderately complex AI products, features and platform enhancements. * Designs advanced test plans covering model accuracy, bias detection, explainability and operational ...

Lead AI Quality Assurance Engineer

Raleigh, NC ยท Hybrid

$125K/yr

Leads testing efforts for moderately complex AI products, features and platform enhancements. * Designs advanced test plans covering model accuracy, bias detection, explainability and operational ...

The company's AI-powered DevSecOps platform automates software releases, improves mobile application testing and security, and provides insights across the software lifecycle. As we enter the Fourth ...

Responsible AI Governance Specialist

Raleigh, NC ยท On-site

$15.75 - $21/hr

Responsible AI Principles Alignment The Responsible AI Governance Specialist will help ensure ... Track governance, testing, and quality assurance evidence, including offline evaluations, human ...

Responsible AI Principles Alignment The Responsible AI Governance Specialist will help ensure ... Track governance, testing, and quality assurance evidence, including offline evaluations, human ...

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Ai Tester information

See Raleigh, NC salary details

$10

$37

$60

How much do ai tester jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for ai tester in Raleigh, NC is $37.29, according to ZipRecruiter salary data. Most workers in this role earn between $20.82 and $49.28 per hour, depending on experience, location, and employer.

What is an AI tester?

An AI Tester is responsible for evaluating artificial intelligence systems to ensure they function correctly, efficiently, and ethically. They design and execute test cases, identify flaws or biases, and verify that AI models meet performance standards. AI Testers work with developers and data scientists to improve AI reliability and user experience. Their role is crucial in preventing errors, reducing risks, and ensuring AI models make accurate and fair decisions.

What are the key skills and qualifications needed to thrive as an AI tester?

To thrive as an AI Tester, you need a background in computer science, experience with software testing methodologies, and a solid understanding of artificial intelligence technologies. Familiarity with testing tools (such as Selenium, Jupyter notebooks, or TensorFlow testing frameworks), programming languages like Python, and relevant certifications (e.g., ISTQB) are highly advantageous. Attention to detail, problem-solving abilities, and strong communication skills help AI Testers identify and articulate issues effectively. These skills ensure AI systems are reliable, accurate, and deliver expected outcomes in real-world applications.

What are some typical challenges faced by AI testers in their daily work?

AI Testers often encounter challenges such as managing and testing large, complex datasets, handling rapidly evolving algorithms, and ensuring consistent test coverage across various real-world scenarios. They must also validate that AI models are free from bias and produce accurate, reproducible results under different conditions. Overcoming these challenges requires both technical proficiency and adaptability. Collaboration with data scientists, developers, and product managers is common, and testers frequently update their testing approaches to keep pace with the fast changes in AI technology.

Can I get an AI Tester job with no experience?

Entry-level AI Tester positions often do not require prior experience, but having basic knowledge of programming, testing tools, and AI concepts can improve your chances. Many employers offer training or are willing to hire candidates with relevant skills or certifications, such as in software testing or machine learning fundamentals.

How do you become an AI tester?

To become an AI tester, you typically need a background in computer science, software testing, or related fields, along with knowledge of machine learning and AI concepts. Gaining experience with programming languages like Python and familiarity with testing tools and frameworks are also important. Certifications in software testing or AI can enhance your qualifications and job prospects.

How much do AI testers make?

AI testers typically earn between $50,000 and $100,000 annually, depending on experience, location, and the complexity of the projects. Entry-level positions may start lower, while experienced testers with skills in automation tools and programming can earn higher salaries.

What are the most commonly searched types of Ai Tester jobs in Raleigh, NC?

The most popular types of Ai Tester jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Ai Tester jobs?

Cities near Raleigh, NC with the most Ai Tester job openings:

Infographic showing various Ai Tester job openings in Raleigh, NC as of August 2026, with employment types broken down into 56% Full Time, 17% Part Time, and 27% Contract. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $77,563 per year, or $37.3 per hour.

AI Training Specialist - Cheminformatics

Cary, NC โ€ข Remote

micro1 AI
Software Developmentย โ€ขย 11 - 50 employees

$80 - $110/hr

Part-time

Posted 29 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 customerโ€™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 โ€” 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, Schrรถdinger, 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.