1

Generative Ai Testing Jobs in Orem, UT (NOW HIRING)

Support testing, configuration management, and source code/change management processes, ensuring ... Proven experience with Generative AI (prompt engineering, fine-tuning, RAG) combined with ...

Support testing, configuration management, and source code/change management processes, ensuring ... Proven experience with Generative AI (prompt engineering, fine-tuning, RAG) combined with ...

Support testing, configuration management, and source code/change management processes, ensuring ... Proven experience with Generative AI (prompt engineering, fine-tuning, RAG) combined with ...

... Generative AI (prompt engineering, fine-tuning, RAG) combined with traditional software engineering skills (API design, CI/CD pipelines, Git). * Exceptional debugging, problem-solving, and testing ...

Senior AI Security Engineer

Lehi, UT · On-site

$130 - $180/hr

Experience evaluating the security of generative AI systems * Experience with cloud platforms ... testing, and post‑accident and reasonable suspicion drug and alcohol testing. EOE AA M/F ...

Senior AI Security Engineer

Lehi, UT · On-site +1

$107K - $147K/yr

Experience evaluating the security of generative AI systems * Experience with cloud platforms ... drug testing, and post-accident and reasonable suspicion drug and alcohol testing. EOE AA M/F ...

Senior AI Security Engineer

Lehi, UT · On-site +1

$107K - $147K/yr

Experience evaluating the security of generative AI systems * Experience with cloud platforms ... drug testing, and post-accident and reasonable suspicion drug and alcohol testing. EOE AA M/F ...

Senior AI Security Engineer

Lehi, UT · On-site +1

$107K - $147K/yr

Experience evaluating the security of generative AI systems * Experience with cloud platforms ... drug testing, and post-accident and reasonable suspicion drug and alcohol testing. EOE AA M/F ...

Senior AI Security Engineer

Lehi, UT · On-site

$107K - $147K/yr

Experience evaluating the security of generative AI systems * Experience with cloud platforms ... drug testing, and post-accident and reasonable suspicion drug and alcohol testing. EOE AA M/F ...

Senior AI Security Engineer

Lehi, UT · On-site +1

$107K - $147K/yr

Experience evaluating the security of generative AI systems * Experience with cloud platforms ... drug testing, and post-accident and reasonable suspicion drug and alcohol testing. EOE AA M/F ...

Evaluate and prioritize Generative AI, predictive analytics, machine learning, and intelligent ... Drive implementation of data quality, testing, monitoring, and operational excellence practices.

Data Scientist

Lehi, UT · On-site

$90 - $130/hr

... or generative AI * Experience with pandas, NumPy, scikit-learn, or similar analytical tools ... Hypothesis Testing * Analytical Problem-Solving * Data Visualization * Cloud-Based AI Services Soft ...

New

As a Junior AI Art Director, you will sit on the cutting edge of art and technology, directly ... Taking initiative to test new generative models and content generation workflows as well as testing ...

next page

Showing results 1-20

Generative Ai Testing information

See Orem, UT salary details

$27

$46

$66

How much do generative ai testing jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for generative ai testing in Orem, UT is $46.71, according to ZipRecruiter salary data. Most workers in this role earn between $38.46 and $53.51 per hour, depending on experience, location, and employer.

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 Orem, UT?

For Generative Ai Testing jobs in Orem, UT, the most frequently searched job titles are:

Infographic showing various Generative Ai Testing job openings in Orem, UT as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $97,152 per year, or $46.7 per hour.

Data Scientist - Applied AI Scientist

Enterprise Technology Operations

Midvale, UT • Hybrid

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 20 days ago


Job description

Zions Bancorporation's Enterprise Technology and Operations (ETO) team is transforming what it means to work for a financial institution. With a commitment to technology and innovation, we have been providing our community, clients and colleagues the best experience possible for over 150 years. Help us transform our workforce of the future, today.

Zions Bancorporation's Innovation Lab is seeking a creative and driven Data Scientist (Applied AI Scientist) who bridges the gap between rigorous statistical research and production-grade software engineering. This role is at the heart of our innovation engine. You will not only uncover deep data insights and design advanced AI algorithms, but you will also architect the robust, scalable code required to bring those concepts to life.

As a key member of the Innovation Lab, you will work in a fast-paced, experimental environment, turning ambiguous business challenges into tangible, data-driven prototypes. We need a scientist who treats machine learning as an engineering discipline, someone who understands the "why" behind the math, and the "how" of robust software implementation.

Visa Sponsorship:
This Data Scientist position is currently NOT eligible for employment visa sponsorship (e.g., H-1B visa). This includes, for example, situations where a candidate may have temporary work authorization while enrolled in school or upon graduation (e.g., CPT, OPT) but would need H-1B visa sponsorship within a few years of employment in order to maintain employment eligibility.

Responsibilities:

  • End-to-End AI Design: Design, prototype, and validate ML/AI solutions, translating complex business challenges into mathematical formulations and scalable, production-ready code.
  • Advanced Analytics & EDA: Perform deep exploratory data analysis, statistical testing, and data transformations on diverse datasets (structured and unstructured) to uncover predictive signals and validate hypotheses.
  • Production-Grade Science: Architect and implement modular, extensible, and testable Python codebases for AI experiments. Move beyond Jupyter notebooks by applying clean-code principles (SOLID, DRY) for seamless hand-off to ETO Engineering teams.
  • Agentic & Generative AI: Develop and experiment with applied generative AI and multi-agent architectures using orchestration frameworks (e.g., LangChain, LangGraph), focusing on optimal state management, robust RAG pipelines, and efficient system design.
  • Algorithmic Optimization: Optimize model inference, data processing pipelines, and memory footprints for latency and scalability, applying a strong understanding of data structures and algorithmic complexity.
  • Rigorous Evaluation: Build automated evaluation frameworks to benchmark model performance, mitigate hallucinations, track drift, and ensure algorithmic fairness via A/B testing and statistical rigor.
  • Collaboration & Communication: Act as the technical translator between research-focused ideation and engineering execution. Communicate complex statistical findings and system architectures to both technical and non-technical stakeholders.

Qualifications:

  • The Scientist's Mind: Solid foundation in statistics (Bayesian/Frequentist), linear algebra, hypothesis testing, and the internal mechanics of ML algorithms (e.g., how optimizers work, loss functions, attention mechanisms).
  • The Engineer's Toolbelt: Advanced Python proficiency with a strong focus on Object-Oriented Programming (OOP) and modular design. You must be comfortable writing unit tests (e.g., Pytest) for your data pipelines and models.
  • Framework Depth: Deep expertise with ML libraries (PyTorch, TensorFlow, Scikit-learn, Pandas) and experience implementing custom logic, rather than just calling out-of-the-box models.
  • Generative AI Systems: Hands-on experience with NLP, Large Language Models (LLMs), and Vector Databases, with an understanding of how to evaluate and optimize these systems at scale.
  • Software Maturity: Proficiency with Git/version control, containerization (Docker), API development (FastAPI/Flask), and a working knowledge of how models fit into a CI/CD lifecycle (MLOps).
  • Problem Solving: Exceptional problem-solving skills, comfort with ambiguity, and the ability to own the data science lifecycle from abstract ideation to engineered prototype.
  • Education & Experience: Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field plus 4+ years of hands-on experience in applied machine learning or data science. A Master's degree or PhD is a plus. A combination of education and experience may meet qualifications.

Location:

This position has a hybrid work from home schedule with a minimum of three days per week in the office at the new Zions Technology Center in Midvale, UT.

The Zions Technology Center is a 400,000-square-foot technology campus in Midvale, Utah. Located on the former Sharon Steel Mill superfund site, the sustainably built campus is the company's primary technology and operations center. This modern and environmentally friendly technology center enables Zions to compete for the best technology talent in the state while providing team members with an exceptional work environment with features such as:

  • Electric vehicle charging stations and close proximity to Historic Gardner Village UTA TRAX station.
  • At least 75% of the building is powered by on-site renewable solar energy.
  • Access to outdoor recreation, parks, trails, shareable bikes and locker rooms.
  • Large modern cafe with a healthy and diverse menu.
  • Healthy indoor environment with ample natural light and fresh air.
  • LEED-certified sustainable building that features include the use of low VOC-emitting construction materials.

Benefits:

  • Medical, Dental and Vision Insurance - START DAY ONE!
  • Life and Disability Insurance, Paid Parental Leave and Adoption Assistance
  • Health Savings (HSA), Flexible Spending (FSA) and dependent care accounts
  • Paid Training, Paid Time Off (PTO) and 11 Paid Federal Holidays
  • 401(k) plan with company match, Profit Sharing, competitive compensation in line with work experience
  • Mental health benefits including coaching and therapy sessions
  • Tuition Reimbursement for qualifying employees
  • Employee Ambassador preferred banking products

#dice

Illusion