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Internship Ai Tester Jobs (NOW HIRING)

Cotiviti

Intern - Generative AI/Agentic AI/Research

$32 - $40/hr

Overview This internship centers on researching and developing advanced healthcare informatics ... testing autonomous AI agents and generative AI systems tailored for healthcare informatics.

Cotiviti

Intern - Generative AI/Agentic AI/Research

$32 - $40/hr

Overview This internship centers on researching and developing advanced healthcare informatics ... testing autonomous AI agents and generative AI systems tailored for healthcare informatics.

Western Aircraft

Structures Internship - SkillBridge

Boise, ID · On-site

$14.25 - $19/hr

... testing, maintenance and repair of aircraft per FAA and manufacturers specifications. Interns will ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Peraton

Generative AI Engineering Intern (Graduate)

$17.25 - $22.25/hr

Interns can support 100% remotely. This open-ended graduate internship is designed to provide ... Support prompt engineering efforts including designing, testing, and refining prompts to improve ...

Makai Labs

AI Engineer

... testing, and evaluation of new approaches • Own smaller projects or sub-projects with guidance ... through internships, coursework, research, or personal projects • Experience running AI ...

Makai Labs

AI Engineer

... testing, and evaluation of new approaches • Own smaller projects or sub-projects with guidance ... through internships, coursework, research, or personal projects • Experience running AI ...

Black Box

AI Intern - Dallas, TX

Plano, TX · On-site

Plano, Texas, USA Internship Duration: 6-12 months (12 months preferred) Company: Black Box ... Support testing, debugging, deployment, and monitoring of AI services on Azure. * Document AI ...

Black Box

AI Engineer Intern - USA

Plano, TX · On-site

Plano, Texas, USA Internship Duration: 6-12 months (12 months preferred) Company: Black Box ... Support testing, debugging, deployment, and monitoring of AI services on Azure. * Document AI ...

Western Aircraft

Avionics Internship - SkillBridge

Boise, ID · On-site

$27.25 - $35.75/hr

Applicants testing positive for the presence of prohibited drugs are ineligible for employment. DOT ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Western Aircraft

Avionics Internship - SkillBridge

Boise, ID

$27.25 - $35.75/hr

Applicants testing positive for the presence of prohibited drugs are ineligible for employment. DOT ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

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Internship Ai Tester information

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How much do internship ai tester jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for internship ai tester in the United States is $47.54, according to ZipRecruiter salary data. Most workers in this role earn between $37.50 and $56.01 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an internship AI tester, and why are they important?

To thrive as an Internship AI Tester, you need a basic understanding of software testing principles, familiarity with AI concepts, and enrollment in or completion of coursework in computer science or a related field. Experience with testing tools like Selenium, Jupyter Notebooks, version control systems (e.g., Git), and knowledge of programming languages such as Python are typically required. Attention to detail, analytical thinking, and effective communication are valuable soft skills that help you identify bugs and collaborate with development teams. These skills are crucial for ensuring AI systems function as intended and deliver reliable results in real-world applications.

What is an internship AI tester?

An Internship AI Tester is a temporary, entry-level position where individuals assist in evaluating and validating artificial intelligence (AI) systems and applications. Their tasks typically involve designing and executing test cases, identifying bugs or issues, and working closely with developers and AI engineers to improve system performance. Interns in this role gain hands-on experience with machine learning models, data analysis, and software testing methodologies. This internship is ideal for students or recent graduates interested in AI, software quality assurance, or related fields.

What is the difference between Internship Ai Tester vs AI Quality Assurance Tester?

AspectInternship Ai TesterAI Quality Assurance Tester
Required CredentialsEnrolled in or recent graduate of relevant field (e.g., computer science, AI)Experience with AI systems, testing, and quality assurance certifications
Work EnvironmentInternship setting, learning-focused, entry-level tasksFull-time or part-time role, focused on testing AI models and systems
Employer & Industry UsageTech companies, startups, research labsTech firms, AI development companies, software testing firms

The main difference is that an Internship Ai Tester is typically an entry-level, learning-focused position for students or recent graduates, while an AI Quality Assurance Tester is a more experienced role responsible for ensuring AI system quality and performance. Interns gain foundational experience, whereas QA testers perform ongoing testing and validation tasks in professional settings.

What types of projects and tasks can I expect to work on as an internship AI tester?

As an Internship AI Tester, you'll typically be involved in testing and evaluating AI-driven software, such as chatbots, recommendation engines, or computer vision applications. Your daily tasks may include writing and executing test cases, reporting bugs, analyzing AI output for accuracy and fairness, and collaborating closely with developers and data scientists to improve product quality. You may also use various testing tools and participate in team meetings to discuss findings and suggest enhancements. This role provides a hands-on opportunity to learn about AI technologies and quality assurance best practices in a collaborative, fast-paced setting.
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Internship Ai Tester jobs near you
Infographic showing various Internship Ai Tester job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution, with an average salary of $98,889 per year, or $47.5 per hour.

AI Engineer, Internship - Summer 2026 - Applications Open Now

Postman

Berkeley, CA

Temporary, Internship

Posted 12 days ago

Job description

The Opportunity (Summer 2026 AI Internship - Applications Open Now)

We're seeking an AI Engineer Intern to work alongside our AI team on large-scale AI and Agentic  systems from data pipeline to production deployment. This role is scoped for someone with foundational experience who wants to deepen it: you'll own discrete pieces of real systems under the mentorship of senior engineers, not shadow work or isolated coursework-style projects.

What You'll Do

You'll work directly with the AI team, taking responsibility for well-scoped pieces of real systems, with mentorship from senior engineers.

Benchmarks & Evaluation

  • Contribute to APIFlow-Bench, our open-source benchmark for real API-development work: design and review benchmark tasks and their mock API environments, extend the evaluation harness and task-generation pipeline in Python, and help maintain the public multi-model leaderboard with statistical confidence intervals.
  • Help build a new action-level AI safety benchmark: instead of grading what a model says, it scores what an agent actually does inside a simulated enterprise API environment. You'll work on scenario design, threat modeling (prompt injection, data exfiltration, permission overreach), and auditable evaluation design.

Model Training & Efficiency

  • Fine-tune open-weight models for tool calling and agentic tasks (SFT, distillation, and RL) using PyTorch and the open-source training ecosystem, on both managed training platforms and self-managed cloud GPUs.
  • Design and run experiments with rigor: evaluate every training run on our benchmarks, support ablation studies and error analysis, track experiments, and report results honestly, including cost.
  • Evaluate ultra-low-bit quantized models for on-device use: extend our quantized vs. full-precision benchmark comparisons and analyze where and why they diverge.

Agent Systems & Engineering Practice

  • Help build the next generation of Postman's in-product AI agent (Agent Mode): a deliberately minimal agent architecture that calls LLM APIs directly (tool loops, multi-step execution, checkpointing), primarily in TypeScript. No prior TypeScript is required; strong Python fundamentals transfer quickly.
  • Read the source code of open-source agent harnesses and turn what you learn into design specs and prototypes.
  • Document experiments, design decisions, and runbooks so your work is legible to the next person; flag safety, fairness, or privacy concerns you observe in model or agent behavior.
About You
  • Currently pursuing a BS, MS, or PhD in Computer Science, Data Science, or a related quantitative field.
  • Hands-on experience training or evaluating ML models: course projects, research, hackathons, or a prior internship all count.
  • Solid Python fundamentals: data structures, functions, basic testing; comfortable writing and reviewing code outside of notebooks.
  • Working knowledge of at least one deep-learning framework (PyTorch preferred).
  • Clear written and verbal communication, and a habit of documenting what you build.
Preferred Qualifications  (none required; the more of these you have, the better)
  • Experience fine-tuning open-weight LLMs (SFT, LoRA, RL, or distillation), with the improvement measured on a benchmark.
  • Experience building LLM agents (tool calling, multi-step loops) or LLM evaluation harnesses/benchmarks, and reporting results with statistical rigor.
  • A track record of shipping real software end-to-end: APIs and services, CLIs, Docker, CI/CD, cloud; public code on GitHub is a big plus.
  • Interest or experience in AI safety and robustness: red-teaming, prompt injection, agent security, fairness, or interpretability.
  • Exposure to model-efficiency work: quantization, low-bit inference, or serving optimization.
  • Evidence of rigor and initiative: publications, technical blog posts, ablation studies, or self-driven side projects with quantified results.
  • Fluency with AI coding tools (Claude Code, Cursor, Codex) to ship fast while still deeply understanding the systems you build.

Apply