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Internship Code Tester Jobs in California (NOW HIRING)

SpaceX

$40/hr

Software coding experience in one or more of the following: C, C++, C#, Java, JavaScript, Python ... Strong skills in debugging, performance optimization and unit testing * Strong interpersonal skills ...

SpaceX

$40/hr

Software coding experience in one or more of the following: C, C++, C#, Java, JavaScript, Python ... Strong skills in debugging, performance optimization and unit testing * Strong interpersonal skills ...

SpaceX

$40/hr

Software coding experience in one or more of the following: C, C++, C#, Java, JavaScript, Python ... Strong skills in debugging, performance optimization and unit testing * Strong interpersonal skills ...

SpaceX

$40/hr

Software coding experience in one or more of the following: C, C++, C#, Java, JavaScript, Python ... Strong skills in debugging, performance optimization and unit testing * Strong interpersonal skills ...

SpaceX

$40/hr

Software coding experience in one or more of the following: C, C++, C#, Java, JavaScript, Python ... Strong skills in debugging, performance optimization and unit testing * Strong interpersonal skills ...

SpaceX

$40/hr

Software coding experience in one or more of the following: C, C++, C#, Java, JavaScript, Python ... Strong skills in debugging, performance optimization and unit testing * Strong interpersonal skills ...

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All JobsCode Tester JobsInternship Code Tester JobsInternship Code Tester Jobs in California

Internship Code Tester information

What does an internship code tester do?

An Internship Code Tester assists software development teams by testing and evaluating code to find bugs, errors, and other issues before software is released. They work closely with developers to understand requirements, execute test cases, and document any problems they discover. This role provides hands-on experience in software testing methodologies, debugging, and quality assurance processes, making it an excellent starting point for a career in software development or QA.

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

To thrive as an Internship Code Tester, you need a basic understanding of programming concepts, software testing methodologies, and a relevant academic background, such as computer science coursework. Familiarity with testing tools like Selenium, JUnit, or Postman, as well as bug tracking systems such as Jira, is often expected. Attention to detail, analytical thinking, and effective communication are crucial soft skills for identifying issues and collaborating with development teams. These competencies ensure accurate defect detection, efficient test execution, and clear reporting, all of which contribute to delivering reliable software products.

What are some common challenges faced by internship code testers, and how can they overcome them?

Internship Code Testers often encounter challenges such as understanding complex codebases, adapting to different testing frameworks, and effectively communicating bugs or issues to developers. To overcome these hurdles, interns should proactively seek clarification from mentors, make use of documentation, and regularly participate in team meetings. Building strong collaboration skills and being open to feedback can also help interns integrate smoothly into the team and accelerate their learning curve.

What is the difference between Internship Code Tester vs Software Tester?

AspectInternship Code TesterSoftware Tester
CredentialsTypically pursuing or recent graduate in Computer Science or related fieldOften requires similar educational background, sometimes with certifications like ISTQB
Work EnvironmentInternship setting, supervised, entry-level tasksFull-time or part-time professional role, more independent
Industry UsageUsed in tech companies, startups, and software firms for trainingCommon across IT, software development, and quality assurance teams

Internship Code Testers are entry-level trainees gaining hands-on experience, while Software Testers are experienced professionals responsible for ongoing quality assurance. The internship role is ideal for beginners, whereas the Software Tester role requires more expertise and independence.

What are the most commonly searched types of Code Tester jobs in California?

The most popular types of Code Tester jobs in California are:

What are popular job titles related to Internship Code Tester jobs in California?

For Internship Code Tester jobs in California, the most frequently searched job titles are:

What job categories do people searching Internship Code Tester jobs in California look for?

The top searched job categories for Internship Code Tester jobs in California are:

What cities in California are hiring for Internship Code Tester jobs?

Cities in California with the most Internship Code Tester job openings:

Internship Code Tester jobs near you
Infographic showing various Internship Code Tester job openings in California as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, and 3% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.

AI Engineer, Internship - Summer 2026 - Applications Open Now

Postman

Berkeley, CA

Temporary, Internship

Re-posted 12 hours 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