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$57

How much do artificial intelligence testing jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for artificial intelligence testing in California is $45.87, according to ZipRecruiter salary data. Most workers in this role earn between $41.54 and $50.29 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals in artificial intelligence testing?

Professionals in Artificial Intelligence Testing often encounter unique challenges, such as validating the unpredictable behavior of machine learning models and ensuring algorithmic fairness and accuracy. They must design comprehensive test cases to cover a wide variety of data inputs and potential edge cases, often in complex, rapidly evolving environments. Collaboration with data scientists, developers, and stakeholders is essential to understand model requirements and to interpret test results accurately. Staying up-to-date with advances in both AI and testing technologies is also key, as the field is continually evolving.

What are the key skills and qualifications needed to thrive in artificial intelligence testing?

To thrive in Artificial Intelligence Testing, candidates typically need a background in computer science, machine learning concepts, software testing methodologies, and knowledge of programming languages like Python or Java. Familiarity with AI testing frameworks, version control systems, and tools such as TensorFlow, PyTorch, or JUnit is highly valued, along with certifications in software testing or AI. Strong problem-solving ability, attention to detail, and effective communication skills are critical soft skills in this role. These qualifications ensure the tester can rigorously validate AI models, collaborate well with development teams, and maintain high-quality, reliable AI systems.

What is an artificial intelligence testing job?

An Artificial Intelligence Testing job involves evaluating and validating AI models, algorithms, and systems to ensure accuracy, reliability, and fairness. Testers design test cases, identify biases, detect errors, and assess model performance under different conditions. They use tools like automation frameworks, data validation techniques, and model debugging to improve AI functionality. The role requires knowledge of machine learning, programming, and testing methodologies to ensure AI systems perform as expected in real-world scenarios.

Is artificial intelligence testing a good career?

Artificial intelligence testing is a growing field that involves evaluating AI systems for accuracy, reliability, and safety. It requires skills in programming, data analysis, and understanding machine learning models, making it a promising career with increasing demand across various industries.

How do I become an artificial intelligence tester?

To become an artificial intelligence tester, you typically need a background in computer science, software testing, or data analysis, along with knowledge of machine learning and AI concepts. Skills in programming languages such as Python or Java, experience with testing tools, and understanding of AI models are important. Earning relevant certifications or completing specialized training can also enhance your qualifications.
What are the most commonly searched types of Artificial Intelligence Testing jobs in California? The most popular types of Artificial Intelligence Testing jobs in California are:
What job categories do people searching Artificial Intelligence Testing jobs in California look for? The top searched job categories for Artificial Intelligence Testing jobs in California are:
What cities in California are hiring for Artificial Intelligence Testing jobs? Cities in California with the most Artificial Intelligence Testing job openings:
Artificial Intelligence Testing jobs near you
Infographic showing various Artificial Intelligence Testing job openings in California as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 10% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $95,400 per year, or $45.9 per hour.

Artificial Intelligence

BridgeNexus Technologies Inc

Los Angeles, CA โ€ข On-site

Other

Posted 4 days ago

Job description

Hi, WE have below 2 positions with our direct client and both are hybrid position and kindly reply asap at your interest so I reach you immediately to schedule one round interview with client .
 
JOB 1:  AI Analyst with Healthcare Background
Location: Woodland Hills. CA (Commute three times in a week to Woodland Hills office)
Duration: Long term
Client: Direct client
JOB 2: AI ML Developer with Data Science experience
Location: Woodland Hills. CA (Commute three times in a week to Woodland Hills office)
Duration: Long term
Client: Direct client 
 
 
 
 
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Role
Job Description
1
AI Analyst with Healthcare Background
seeking an experienced Artificial Intelligence & Machine Learning (AI/ML) Systems Analyst to bridge the gap between business stakeholders, data scientists, AI/ML engineers, and technology teams. This role will be responsible for analyzing business problems, defining AI/ML solution requirements, evaluating data readiness, supporting model implementation, and ensuring AI solutions align with business objectives, regulatory requirements, and enterprise governance standards. The ideal candidate will possess strong analytical skills, healthcare domain knowledge, and experience working with AI, machine learning, and Generative AI technologies.
Key Responsibilities
Business & Systems Analysis
  • Collaborate with business stakeholders to identify opportunities for AI/ML-driven process improvements and automation.
  • Elicit, analyze, and document business, functional, and non-functional requirements.
  • Create user stories, process flows, use cases, data mappings, and acceptance criteria.
  • Translate business requirements into AI/ML solution specifications.
  • Support backlog grooming, sprint planning, and Agile delivery processes.
AI/ML Solution Analysis
  • Partner with AI/ML engineers and data scientists to define model objectives and success metrics.
  • Analyze data sources and determine data quality, completeness, and readiness for AI initiatives.
  • Support predictive analytics, recommendation systems, NLP, GenAI, and intelligent automation initiatives.
  • Evaluate AI model outputs and assist with validation, testing, explainability, and business adoption.
Data & Analytics

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