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Generative Ai Testing Jobs in California (NOW HIRING)

Icwgroup

Applied AI Engineer

San Diego, CA · On-site

Implement end-to-end generative AI solutions, including model fine-tuning, deployment, and testing in production environments. * Collaborate with cloud engineering, AI, and ML Ops teams to ...

Hitachi

AI and Data Engineer

Santa Clara, CA · On-site +1

$29/hr

... edge Generative AI Platform. As an AI and Data Engineer, you will be responsible for designing, testing, and optimizing prompts that enable our AI models to generate high-quality, contextual, and ...

Hitachi, Ltd.

AI and Data Engineer

Santa Clara, CA · On-site

$134K - $161K/yr

... edge Generative AI Platform. As an AI and Data Engineer, you will be responsible for designing, testing, and optimizing prompts that enable our AI models to generate high-quality, contextual, and ...

ICW Group

Applied AI Engineer

San Diego, CA

Implement end-to-end generative AI solutions, including model fine-tuning, deployment, and testing in production environments. * Collaborate with cloud engineering, AI, and ML Ops teams to ...

ICW Group

Applied AI Engineer

San Diego, CA · On-site

Implement end-to-end generative AI solutions, including model fine-tuning, deployment, and testing in production environments. * Collaborate with cloud engineering, AI, and ML Ops teams to ...

Icwgroup

Applied AI Engineer

San Diego, CA

Implement end-to-end generative AI solutions, including model fine-tuning, deployment, and testing in production environments. * Collaborate with cloud engineering, AI, and ML Ops teams to ...

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Generative Ai Testing information

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How much do AI testers get paid?

AI testers, involved in evaluating and validating generative AI models, typically earn salaries ranging from $60,000 to $120,000 annually depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in machine learning and data analysis can earn higher wages.

Is AI testing a good career?

AI testing, including roles like Generative AI Testing, is a growing field with increasing demand for skills in machine learning, data analysis, and programming. It offers opportunities in tech companies, research labs, and startups, often requiring knowledge of AI frameworks and testing tools. The career can be stable and rewarding for those with technical expertise and an interest in AI development and quality assurance.

What are the key skills and qualifications needed to thrive as a Generative AI Testing Specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or executive positions, often requiring advanced skills, extensive experience, and sometimes specialized certifications. These roles usually involve leading AI development projects, strategic planning, and overseeing AI teams in large organizations or tech companies.

How do I become an AI tester?

To become an AI tester, you should have a strong understanding of machine learning concepts, programming skills in languages like Python, and experience with data annotation and model evaluation. Familiarity with AI development tools and testing frameworks, along with attention to detail, is essential for identifying issues in AI systems.

What is Generative AI Testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.
What are popular job titles related to Generative Ai Testing jobs in California? For Generative Ai Testing jobs in California, the most frequently searched job titles are:
What job categories do people searching Generative Ai Testing jobs in California look for? The top searched job categories for Generative Ai Testing jobs in California are:
What cities in California are hiring for Generative Ai Testing jobs? Cities in California with the most Generative Ai Testing job openings:
Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in California as of June 2026, with employment types broken down into 13% Internship, 68% Full Time, 13% Part Time, and 6% Temporary. Highlights an 75% In-person, 6% Hybrid, and 19% Remote job distribution.
Generative AI Analyst (Chinese zh-CN) - Onsite \u007C San Jose, CA

Generative AI Analyst (Chinese zh-CN) - Onsite \u007C San Jose, CA

Welo Data

Sunnyvale, CA

$136K/yr

Full-time

Posted 29 days ago

Job description

About the Role

We are looking for highly detail-oriented Generative AI Analysts to join our team onsite in San Jose, California. In this role, you will contribute to the development of cutting-edge AI technologies by supporting the annotation, evaluation, and quality review of multilingual and multimodal datasets used to train generative AI systems.

This position is ideal for candidates passionate about AI, language, data quality, and emerging technologies, with strong analytical skills and native-level Chinese proficiency.

What You’ll Do
  • Perform annotation and labeling tasks for Chinese generative AI datasets, including text, image, video, audio, and multimodal content
  • Review and evaluate AI-generated prompts and responses across a variety of topics and use cases
  • Conduct quality assurance checks to ensure accuracy, consistency, and compliance with annotation guidelines
  • Identify edge cases, inconsistencies, and quality issues in datasets and model outputs
  • Support data categorization, tagging, evaluation, and content review workflows for machine learning systems
  • Assist in the creation and refinement of annotation guidelines and evaluation frameworks
  • Collaborate with cross-functional teams to improve operational processes and annotation quality
  • Provide feedback on tools, workflows, and annotation methodologies
Requirements
  • Native-level proficiency in Chinese and strong English communication skills (written and verbal)
  • Excellent attention to detail and ability to follow complex guidelines and processes
  • Strong interest in generative AI, machine learning, and emerging technologies
  • Previous experience in data annotation, content review, quality assurance, or labeling operations is preferred
  • Bachelor’s degree or equivalent practical experience
  • Experience or academic background in Finance, STEM, Legal, Medical, Coding, or other specialized fields is highly valued.
  • Ability to work onsite full-time in San Jose, CA
Ways to Stand Out from the Crowd
  • Familiarity with generative AI systems, LLMs, RLHF, or multimodal AI workflows
  • Experience evaluating prompts, responses, images, videos, or AI training datasets
  • QA/testing experience within AI, data operations, or content moderation environments
  • Experience with taxonomy creation, evaluation rubrics, or dataset quality initiatives
  • Python or scripting knowledge
  • Additional language proficiency is a plus (Korean, Japanese, Mandarin, Spanish, German, French, etc.)
Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.
 
To know more details (Click here)
 
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.
 
 
As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
 
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.