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Generative Ai Testing Jobs in California (NOW HIRING)

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 ...

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 ...

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 ...

This role focuses on creating advanced AI applications, including Generative AI systems like ... Ensure code quality and maintainability through unit testing, code reviews, and adherence to best ...

Experience shipping AI-native product features that expose generative AI to end users. Bonus Points ... testing, and "boring" quality work. * You're skeptical of AI tools, or you'd rather write Jira ...

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Generative Ai Testing information

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 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 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 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 do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Relevant certifications and hands-on projects can enhance your qualifications for roles in AI testing environments.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development, focusing on evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, often involving tools like Python and TensorFlow. The role offers opportunities in tech companies and research labs, with demand expected to increase as AI applications expand.

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:

Infographic showing various Generative Ai Testing job openings in California as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, 5% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Software Engineer III, Generative AI, Search AI Labs

Mountain View, CA • On-site

Google Inc.
Software Development • 10K+ employees

$67.25 - $90.50/hr

Other

Posted 2 days ago

New


Google rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz


Job description

Software Engineer III, Generative AI, Search AI Labs

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Google Mountain View, CA, USA Mid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

  • Bachelor's degree or equivalent practical experience.
  • 2 years of experience with software development in Python or C++ programming languages, or 1 year of experience with an advanced degree.
  • 2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models).
Preferred qualifications:
  • Master's degree or PhD in Computer Science or related technical fields.
  • Experience building software solutions utilizing Generative AI agents and Large Language Models (LLMs) and applying them to automation.
  • Experience with Search Infrastructure, Search Quality, or large language models (LLMs).
  • Experience navigating complex systems, debugging, and resolving difficult technical issues.
  • Ability to start in MTV 6 weeks from offer accept.
  • Strong communication, leadership, and cross-functional collaboration skills.
About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. In Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

  • Deliver end-to-end capabilities to support GenAI development, including advanced prompt tuning tools, context generation approaches, quality loss mitigation, and new development technologies.
  • Partner with broader Search teams to solve complex technical issues, applying LLM technologies to improve Search developer experience and accelerate Search feature development velocity.
  • Collaborate effectively with PMs and other engineers to translate user requirements and developer workflows into highly effective, stable, and production-ready tools.
  • Identify new areas of improvement, proposing innovative solutions to enhance the developer experience and solve critical bottlenecks in the Search GenAI feature quality hill-climbing process.
  • Execute projects in alignment with the team's roadmap, ensuring high-quality code, testing, and timely delivery.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They

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