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Generative Ai Testing Jobs in San Rafael, CA (NOW HIRING)

Writer

Software engineer, generative AI

San Francisco, CA · On-site

$111K - $304K/yr

As a software engineer, generative ai at WRITER, you'll be at the forefront of expanding human ... Early-detection cancer testing through Galleri * Flexible spending account and dependent FSA ...

Vivodyne

AI Senior Scientist

San Francisco, CA · Hybrid

Domain & Technical Growth - Remain current with the latest research trends in Generative AI ... with continuous testing and governance compliance. * Resource Optimization - Apply financial ...

Vivodyne

AI Senior Scientist

San Francisco, CA · On-site

We accelerate the successful discovery, design, and development of human therapeutics by testing on ... Domain & Technical Growth - Remain current with the latest research trends in Generative AI ...

Nexxa.ai

Applied AI Engineer

San Francisco, CA · On-site

... Generative AI , Computer Vision , and Machine Learning . This role is a blend of software ... Lead full project lifecycles: scoping, solution design, development, implementation, testing ...

Writer

AI deployment engineer (West)

San Francisco, CA · On-site

$131K - $185K/yr

... generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Seattle, Austin ... Early-detection cancer testing through Galleri * Flexible spending account and dependent FSA ...

Erth.AI Inc.

Research Engineer

San Francisco, CA · On-site

$120K - $200K/yr

Utilize rigorous testing and iterative improvement processes to optimize the performance and ... Experience with LLMs and imaginative generative AI. * Participation in research projects/papers ...

Erth.AI Inc.

Research Engineer

San Francisco, CA · On-site

$120K - $200K/yr

Utilize rigorous testing and iterative improvement processes to optimize the performance and ... Experience with LLMs and imaginative generative AI. * Participation in research projects/papers ...

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Generative Ai Testing information

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How much do generative ai testing jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for generative ai testing in San Rafael, CA is $59.89, according to ZipRecruiter salary data. Most workers in this role earn between $49.33 and $68.61 per hour, depending on experience, location, and employer.

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 software quality assurance. 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.

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 is the salary of generative AI tester?

The salary of a generative AI tester typically ranges from $70,000 to $120,000 annually, depending on experience, location, and company size. Entry-level positions may start lower, while experienced testers with specialized skills in AI and machine learning can earn higher salaries. Certifications in AI or related fields can also influence compensation.

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.

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 tools, testing frameworks, and quality assurance processes is also important. Gaining relevant certifications or training in AI and software testing can enhance your qualifications.

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 cities near San Rafael, CA are hiring for Generative Ai Testing jobs? Cities near San Rafael, CA with the most Generative Ai Testing job openings:
Generative Ai Testing jobs near you
ML Engineer - Generative AI

ML Engineer - Generative AI

Dream Technologies Inc

San Francisco, CA • On-site

Full-time

Re-posted 2 days ago

Job description

We are looking for a Generative AI engineer to work on the full lifecycle of novel spatial generative AI model development, defining the correct frame of an inference problem, structuring image-based training data into usable formats, training and testing models, deploying performant systems into our production architecture stack.
Upcoming Challenges
  • Generate high quality renovation and home design layouts using state-of-the-art generative models.
  • Build a model that adapts to user feedback and suggests home design tailored to user preferences.
  • Define required datasets and work with labeling agencies to generate high quality data.
  • Deploy models to production environments and iterate with real users on real-world problems.

What we Require
  • MS in Computer Science with a focus or specialty in Machine Learning
  • 2+ Years of experience training and deploying real-world AI . Deep understanding of model architectures, training pipelines, and evaluation methodologies.
  • Creativity and technical depth to explore, evaluate, and iterate on different machine learning approaches
  • Scrappiness and speed in getting models built and tested under real-world constraints.
  • Strong background in algorithms, data structures, and mathematics, with the ability to design performant solutions to spatial and generative problems.
  • Proficiency in Python, with a strong preference for experience using NumPy and PyTorch.

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