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Part Time Ai Tester Jobs (NOW HIRING)

Weekday AI

Risk & Actuarial AI Expert

$100 - $120/hr

... Type: Part-time / Contract Location: US, UK, Canada, France, Portugal (remote) We are seeking a ... You will also contribute to stress testing, scenario planning, and regulatory reporting ...

The Pennsylvania State University

As a part-time Nittany AI Intern, you will work alongside the full-time tech lead and program ... Experience with version control, documentation, testing, or Agile workflows is a plus Additional ...

Braze

Senior Lead AI Solutions Consultant

New York, NY · On-site

$130K - $195K/yr

Serve as a thought leader, evangelizing the benefits of AI testing & reinforcement learning ... In addition to cash compensation, Braze offers full- and part- time employees a comprehensive Total ...

Braze

Senior Lead AI Solutions Consultant

Chicago, IL · On-site

$124K - $186K/yr

Serve as a thought leader, evangelizing the benefits of AI testing & reinforcement learning ... In addition to cash compensation, Braze offers full- and part- time employees a comprehensive Total ...

N2IA Technologies

AI Developer

San Juan, PR · Remote

Responsibilities include assisting with the design, development, and testing of applications ... Certifications in AWS Schedule: * Part Time Position: 10 hours per week * Location: 100% Remote ...

Booz Allen Hamilton, Inc.

AI/ML Engineer

Hampton, VA · On-site

Experience adding testing and security scans to pipelines * Secret clearance * Bachelor's degree ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Amwins Internships

Analytics & AI Intern

Windsor, CT · On-site

$22/hr

Aug -Dec 2026 or Fall term Hourly Rate: $22 Hours: Part-time (20 hrs.), non-exempt Location ... Assist with testing, documenting, and improving the solutions we build. · Collaborate with ...

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Part Time Ai Tester information

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How much do part time ai tester jobs pay per hour?

As of Jul 25, 2026, the average hourly pay for part time ai tester in the United States is $38.36, according to ZipRecruiter salary data. Most workers in this role earn between $21.39 and $50.72 per hour, depending on experience, location, and employer.

What are part time AI testers?

Part time AI testers are professionals who evaluate artificial intelligence systems or applications on a part-time basis. Their main responsibilities include testing AI models for accuracy, usability, bias, and functionality, as well as reporting bugs or issues to the development team. Part time positions allow for flexible hours, making this role suitable for students, freelancers, or those seeking additional income. AI testers may work with chatbots, image recognition tools, recommendation systems, or other types of AI products. They often need to document their findings and provide feedback to help improve the AI’s performance.

What is the difference between Part Time Ai Tester vs Part Time Data Annotator?

AspectPart Time Ai TesterPart Time Data Annotator
CredentialsBasic technical skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or office-based, testing AI modelsRemote or office-based, labeling data
Industry UsageAI development, machine learning projectsData preparation, machine learning datasets

Both roles involve data handling and require attention to detail, but Part Time Ai Testers focus on evaluating AI model performance, while Part Time Data Annotators primarily label and prepare data for training AI systems.

What are the key skills and qualifications needed to thrive as a Part Time AI Tester, and why are they important?

To thrive as a Part Time AI Tester, you need analytical thinking, attention to detail, and a basic understanding of software testing principles, often supported by some technical or computer science background. Familiarity with testing tools, bug tracking systems, and basic scripting languages like Python is typically required. Strong communication, problem-solving abilities, and adaptability help testers report issues clearly and collaborate effectively with development teams. These skills ensure accurate identification of AI system flaws and contribute to delivering reliable, high-quality artificial intelligence products.

What are some typical challenges faced by part-time AI testers, and how can they effectively manage their workload?

Part-time AI testers often face challenges such as adapting quickly to new testing protocols, managing shifting project priorities, and staying updated on evolving AI models. Since their hours are limited, it is crucial to communicate clearly with team leads about task expectations and deadlines. Effective time management, staying organized with detailed notes, and leveraging collaboration tools can help part-time testers contribute meaningfully while maintaining work-life balance. Additionally, proactively seeking feedback and participating in briefings can keep testers in sync with full-time colleagues and project goals.
More about Part Time Ai Tester jobs
What cities are hiring for Part Time Ai Tester jobs? Cities with the most Part Time Ai Tester job openings:
What are the most commonly searched types of Ai Tester jobs? The most popular types of Ai Tester jobs are:
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Part Time Ai Tester jobs near you
Infographic showing various Part Time Ai Tester job openings in the United States as of July 2026, with employment types broken down into 100% Part Time. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $79,791 per year, or $38.4 per hour.

Risk & Actuarial AI Expert

Weekday AI

Remote

$100 - $120/hr

Part-time

Posted 5 days ago

Job description

This role is for one of our clients
Compensation: $100-$120 per hour (20 hours per week commitment)
Job Type: Part-time / Contract
Location: US, UK, Canada, France, Portugal (remote)
We are seeking a highly analytical and forward-thinking Risk & Actuarial AI Expert to join our growing team. This role sits at the intersection of actuarial science, risk management, and advanced analytics, leveraging artificial intelligence to enhance decision-making across insurance and risk portfolios. The ideal candidate will bring a strong foundation in actuarial principles combined with hands-on experience in data science, enabling the transformation of complex risk data into actionable insights.
Requirements
Key Responsibilities:
You will play a central role in evaluating and optimizing portfolio performance through detailed loss ratio and combined ratio analysis. This includes monitoring trends, identifying deviations, and providing recommendations to improve underwriting profitability. A deep understanding of claims behavior, pricing adequacy, and expense structures will be critical to success in this area.
In addition, you will conduct comprehensive portfolio risk assessments, using statistical models and AI-driven techniques to evaluate exposure across various lines of business. This involves identifying risk concentrations, assessing diversification, and supporting strategic decisions related to risk selection and capital allocation. You will collaborate closely with underwriting, finance, and product teams to ensure alignment between risk appetite and business objectives.
A significant part of the role will focus on catastrophe modeling and exposure management. You will work with catastrophe models and geospatial data to assess potential losses from natural disasters and extreme events. Enhancing traditional modeling approaches using machine learning techniques to improve prediction accuracy and scenario analysis will be a key expectation. You will also contribute to stress testing, scenario planning, and regulatory reporting requirements.
AI & Analytics Integration:
The role requires leveraging modern AI/ML techniques to automate actuarial workflows, improve predictive modeling, and uncover hidden patterns in large datasets. You will design and implement models that enhance pricing, reserving, and risk selection processes. Experience with tools such as Python, R, and cloud-based analytics platforms will be valuable.
Qualifications & Skills:
  • Bachelor's or Master's degree in Actuarial Science, Mathematics, Statistics, Data Science, or a related field
  • Progress toward actuarial certification (e.g., IFoA, SOA, or equivalent) preferred
  • 2-8 years of experience in actuarial analysis, risk management, or insurance analytics
  • Strong expertise in loss ratio and combined ratio analysis
  • Proven experience in portfolio risk assessment and risk modeling
  • Hands-on experience with catastrophe modeling tools and exposure management frameworks
  • Proficiency in programming (Python/R) and data visualization tools
  • Familiarity with machine learning techniques and their application in insurance
  • Strong problem-solving skills and ability to communicate complex insights to non-technical stakeholders

What We're Looking For:
We value individuals who combine technical rigor with business intuition. You should be comfortable working in a dynamic environment, handling ambiguity, and driving innovation through data. A proactive mindset, attention to detail, and the ability to translate analytical findings into strategic recommendations will set you apart in this role.

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