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Generative Ai Testing Jobs in Riverside, CA (NOW HIRING)

Experience with software engineering fundamentals: design patterns, automated testing, code review ... Recent experience utilizing Generative AI techniques including GitHub Copilot and Prompt ...

Experience with software engineering fundamentals: design patterns, automated testing, code review ... Recent experience utilizing Generative AI techniques including GitHub Copilot and Prompt ...

Experience with software engineering fundamentals: design patterns, automated testing, code review ... Recent experience utilizing Generative AI techniques including GitHub Copilot and Prompt ...

Experience with software engineering fundamentals: design patterns, automated testing, code review ... Recent experience utilizing Generative AI techniques including GitHub Copilot and Prompt ...

Experience with software engineering fundamentals: design patterns, automated testing, code review ... Recent experience utilizing Generative AI techniques including GitHub Copilot and Prompt ...

Machine Learning Engineer II

Irvine, CA

$104K - $143K/yr

... models, and generative AI systems. We are seeking a candidate who has hands-on experience ... Agile software development, test-driven development, unit testing, code reviews, design ...

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Generative Ai Testing information

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How much do generative ai testing jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for generative ai testing in Riverside, CA is $56.05, according to ZipRecruiter salary data. Most workers in this role earn between $46.15 and $64.18 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 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 Riverside, CA? For Generative Ai Testing jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Generative Ai Testing jobs in Riverside, CA look for? The top searched job categories for Generative Ai Testing jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Generative Ai Testing jobs? Cities near Riverside, CA with the most Generative Ai Testing job openings:
Sr. Platform Engineer

Other

Retirement, PTO

Posted 6 days ago


Job description

About Origence
With 30 years at the forefront of fintech innovation, Origence delivers SaaS lending solutions that power credit unions across the United States. Our mission is to enable accessible, competitive lending while strengthening the financial ecosystem for credit unions, their members, and dealer partners.
We operate with a customer-first mindset and a culture of ownership, accountability, and operational excellence. We invest in our people and empower them to innovate, improve, and drive measurable business impact.
About You
You are a self-driven, accountable professional who thrives in a fast-moving environment. You operate with an ownership mindset, are comfortable with ambiguity, and focus on solving business problems through automation, data, and process improvement. You are highly collaborative, detail-oriented, and motivated by measurable impact.
The Sr. Platform Engineer will be responsible for designing, building, and maintaining internal tools and platform capabilities that accelerate software delivery across the organization. This is a software engineering role - you will write production-quality code, design APIs, build automation frameworks, and develop self-service tooling applied to platform and infrastructure problems. You will work across CI/CD pipeline engineering, observability platforms, internal developer portals, infrastructure automation, and developer productivity tooling.
What You'll Be Doing
  • Build and maintain YAML-based CI/CD pipeline templates in Azure DevOps used by dozens of teams and hundreds of services.
  • Design and develop internal tools, CLIs, and REST APIs that enable self-service for product development teams (e.g., automated onboarding, pipeline generation, environment provisioning).
  • Write and maintain Terraform modules for Azure cloud infrastructure, including Container Apps, API Management, networking, and disaster recovery.
  • Extend and integrate Datadog monitoring, build custom dashboards, automate alerting, and instrument platform telemetry using OpenTelemetry patterns.
  • Help build and evolve our Internal Developer Portal (IDP) to give developers a unified view of their services, deployments, health, and documentation.
  • Help legacy systems adopt modern CI/CD, Blue/Green deployments, and DR capabilities through template-driven approaches.
  • Build automated compliance gates and security checks that let teams move fast without moving dangerously.
  • Collaborate directly with product developers to understand workflows, reduce friction, and deliver platform capabilities that meet real needs.
  • Spend the majority of your time actively designing and coding. A portion of your time will be spent researching new technology and mentoring other engineers.
The Ideal Candidate
Education:
  • Bachelor's degree in Computer Science, Engineering or related industry experience.
Experience:
  • A minimum of 5 years of professional software engineering experience - you have built and shipped production applications, not just configured infrastructure.
  • Strong proficiency in at least one general-purpose language: C#/.NET, Python, or TypeScript/Node.js.
  • Experience with software engineering fundamentals: design patterns, automated testing, code review, version control, and CI/CD as a practitioner.
  • Azure cloud experience - working knowledge of Azure services (Container Apps, App Services, Azure DevOps, API Management, or similar).
  • Hands-on experience with Terraform (preferred) or equivalent Infrastructure-as-Code tools.
  • Experience designing and building REST APIs or automation services.
  • Recent experience utilizing Generative AI techniques including GitHub Copilot and Prompt Engineering techniques.
Preferred Experience:
  • Experience building internal developer tools, platforms, or productivity tooling.
  • Datadog, OpenTelemetry, or other observability platform experience.
  • Azure DevOps pipeline authoring (YAML templates, variable groups, service connections).
  • Experience with developer portals (Backstage, Cortex, or similar).
  • Familiarity with containers and orchestration (Docker, Kubernetes, Azure Container Apps).
  • Experience working in a platform engineering, SRE, or developer experience team.
  • PowerShell scripting for Windows-based enterprise environments.
  • Financial services or regulated industry experience.
Specialized Skills:
  • Ownership and accountability mindset with strong decision-making, communication, and analytical skills.
  • Can effectively lead technical initiatives and collaborate on design/requirements while gathering the necessary information for development.
  • Ability to write clear documentation, explain technical decisions, and collaborate across teams.
  • Knowledge of various LLMs, Agentic AI, RAG, MCP and incorporating these technologies from both automation and feature engineering standpoints.
  • Understanding of Agile methodologies, Domain Driven Design, and event-driven architecture approaches.
  • Deep expertise in their chosen technology stack with broader knowledge of various programming languages, frameworks, and tools.
  • Ability to break up larger projects into individual pieces, assess complexity of each piece, and balance work amongst team members.
  • Ability to work in a fast-paced / flexible environment that practices SAFe / Agile based SDLC.
  • Sets high standards for behavior and performance, models the values and principles of the organization, and inspires others through action.
Why you should apply:
  • Flexible Working Environment
  • Paid Time Off
  • 401k (8% match)
  • College Tuition Benefits/ Tuition Reimbursement
  • Good Benefits options
  • Company Culture! Cultural and Holiday celebrations, Theme days like Star Wars Day & Bring your Kids to Work Day, Monthly Townhalls and Quarterly Company Meetings that ensure awareness, inclusion, and transparency.

The starting salary range for this full-time position in Irvine, CA is $128600 - $160800 per year. This base pay will take into consideration internal equity, candidate's geographic region, job-related knowledge and experience among other factors. Origence maintains a highly competitive compensation program. Under company guidelines, this position is eligible for an annual bonus to provide an incentive to achieve targeted goals. Bonuses are awarded at company's discretion on an individual basis.
Origence is an equal opportunity employer. All recruitment, hiring, training, compensation, benefits, discipline, and other terms and conditions of employment will be based upon an individuals' qualifications regardless of race, religion, color, sex, gender identity, sexual orientation, national origin, ancestry, military service, marital status, pregnancy, age, protected medical condition, genetic information, disability or any other category protected by federal, state or local law.