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Artificial Intelligence Testing Jobs (NOW HIRING)

GXM Consulting

Artificial Intelligence (AI) Lead Tester

$120K - $180K/yr

GXM Technologies is seeking an Artificial Intelligence (AI) Lead Tester to provide both hands-on ... This role requires both AI technical testing proficiency and automation experience. This position ...

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How much do artificial intelligence testing jobs pay per hour?

As of Jul 8, 2026, the average hourly pay for artificial intelligence testing in the United States is $46.47, according to ZipRecruiter salary data. Most workers in this role earn between $42.07 and $50.96 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 the Artificial Intelligence Testing position, and why are they important?

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.

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What cities are hiring for Artificial Intelligence Testing jobs? Cities with the most Artificial Intelligence Testing job openings:
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Artificial Intelligence Testing jobs near you
Infographic showing various Artificial Intelligence Testing job openings in the United States as of July 2026, with employment types broken down into 5% Internship, 78% Full Time, 5% Part Time, 2% Temporary, and 10% Contract. Highlights an 90% In-person, and 10% Remote job distribution, with an average salary of $96,666 per year, or $46.5 per hour.
AVP, Artificial Intelligence

AVP, Artificial Intelligence

Credit One Bank

Las Vegas, NV • On-site

Full-time

Re-posted 10 days ago

Job description

Job Summary:
Credit One Bank is a data-driven financial services company based in Las Vegas. The Assistant Vice President of Artificial Intelligence is responsible for leading the delivery and execution of AI and machine learning capabilities within a regulated banking environment, focusing on fraud prevention, credit risk management, and customer experience personalization.
Responsibilities:
• Lead development and deployment of AI/ML and Generative AI solutions for fraud detection, credit scoring, underwriting, AML, and customer engagement.
• Serve as technical authority for model architecture, feature engineering, training pipelines, and inference services.
• Manage and mentor AI Engineers and ML practitioners; provide code and design reviews.
• Implement AIOps/MLOps and model governance practices aligned with banking regulations and internal Model Risk Management (MRM) standards.
• Partner with Risk, Compliance, Legal, Cybersecurity, and Data teams to ensure Responsible AI adoption.
• Oversee model validation, explainability, bias testing, and audit readiness.
• Collaborate with product and business leaders to translate financial use cases into scalable AI solutions.
Qualifications:
Required:
• Lead development and deployment of AI/ML and Generative AI solutions for fraud detection, credit scoring, underwriting, AML, and customer engagement.
• Serve as technical authority for model architecture, feature engineering, training pipelines, and inference services.
• Manage and mentor AI Engineers and ML practitioners; provide code and design reviews.
• Implement AIOps/MLOps and model governance practices aligned with banking regulations and internal Model Risk Management (MRM) standards.
• Partner with Risk, Compliance, Legal, Cybersecurity, and Data teams to ensure Responsible AI adoption.
• Oversee model validation, explainability, bias testing, and audit readiness.
• Collaborate with product and business leaders to translate financial use cases into scalable AI solutions.
• Machine Learning & Modeling: Supervised, unsupervised, reinforcement learning; Deep learning (CNNs, RNNs, Transformers); Natural Language Processing (NLP) & LLMs; Generative AI (diffusion models, fine-tuning, RAG); AI Engineering & MLOps.
• AI Engineering & MLOps: Model training, deployment, monitoring, and retraining; Feature stores, vector databases, and model registries; CI/CD pipelines for ML (MLOps); GPU/accelerator compute architectures.
• Cloud & Infrastructure: Azure AI, Azure ML, AWS Sagemaker, or Google Vertex AI; Kubernetes, containerization, microservices; Data platforms (Databricks, Snowflake, Synapse).
• Responsible AI & Governance: Model explainability (SHAP, LIME); Fairness, bias detection, model risk controls; Privacy-preserving ML techniques (differential privacy, federated learning).
• Programming & Tooling: Python, PyTorch, TensorFlow, JAX; LangChain, semantic search, vector embeddings; Prompt engineering & LLM orchestration frameworks.
• Excellent communication, problem-solving, and project management skills.
• Ability to collaborate effectively and follow up ensure achievement of deadlines, outcomes and results.
• Demonstrate company core values of excellence, ownership, collaboration, and integrity.
Preferred:
• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
• 5-8 + years of experience in AI/ML or data science.
• Experience working with large-scale financial or transactional data is preferred.
Company:
Credit One Bank is a financial services company that offers credit cards, credit score tracking, and fraud protection services. Founded in 1984, the company is headquartered in Las Vegas, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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