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Generative Ai Testing Jobs in Portland, OR (NOW HIRING)

Cambia Health Solutions

AI Scientist Senior II

Portland, OR · On-site

$150 - $190/hr

Expert in generative AI, machine learning, deep learning, and advanced AI/ML techniques. * Proficient in Python, software engineering principles (design patterns, testing, CI/CD), and MLOps. * Strong ...

Netflix

CG Experimental Artist

Vancouver, WA

$47.01/hr

Support a team of CG and Generative AI experts to develop unique content for animated shorts and ... Help testing and expanding upon new GenAI/traditional hybrid workflows developed by other artists ...

Aprio

Senior AI Product Associate, IT

Portland, OR · On-site +1

$104K - $160K/yr

Familiarity with generative-AI tools and platforms, including hands-on prompting and testing of AI APIs. * Ability to quickly learn new domains and translate complex workflows into product ...

Pwc

AI Engineer

Portland, OR

$50K - $112K/yr

... Applying generative AI techniques, including prompt engineering, LLM evaluation, and fine-tuning ... testing, and adversarial benchmarking, to assess reasoning, tool-calling reliability, and output ...

Nvidia

Senior Applied AI Engineer

Hillsboro, OR · On-site

$113K - $156K/yr

If you're passionate about the latest research and cutting-edge technologies shaping generative AI ... design, testing, CI/CD, code quality, observability, security, databases, containers, and ...

Deloitte

AI Security Engineer Manager

Portland, OR

Integrate security across the SSDLC, including code reviews, testing, and deployment. In this role ... and Generative AI solutions. You will operate hands-on across high-visibility initiatives ...

Deloitte

Cyber Full Stack Manager

Portland, OR

Leading the design, development, integration, deployment, testing, and troubleshooting of production-grade solutions within client environments, including artificial intelligence (AI) and generative ...

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Generative Ai Testing information

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How much do generative ai testing jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for generative ai testing in Portland, OR is $56.98, according to ZipRecruiter salary data. Most workers in this role earn between $46.92 and $65.24 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 Portland, OR?

For Generative Ai Testing jobs in Portland, OR, the most frequently searched job titles are:

What job categories do people searching Generative Ai Testing jobs in Portland, OR look for?

The top searched job categories for Generative Ai Testing jobs in Portland, OR are:

Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Portland, OR as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $118,512 per year, or $57 per hour.

AI Scientist Senior II

Portland, OR • On-site

Cambia Health Solutions
Health Care and Social Assistance • 1 - 5K employees

8.4

Company rating: 8.4 out of 10

Based on 32 frontline employees who took The Breakroom Quiz

121st of 311 rated insurance

People enjoy working here

Good employer

Paid breaks

Learn more about Cambia Health Solutionsexternal

Full-time

Re-posted 14 days ago

Job description

AI Scientist Senior II
Hybrid role (3 days/week in office) at our Burlington, Renton, Spokane, Vancouver, Portland, Medford, Salt Lake City, Boise, Lewiston, or Fargo offices.
Candidates must reside within commutable distance of that location or be willing to relocate.
Build a career with purpose. Join our Cause to create a person-focused and economically sustainable health care system.
Who We Are Looking For:
Every day, Cambia's Applied AI Team is living our mission to make health care easier and lives better. AI Scientists work with various stakeholders to design, develop, and implement data-driven solutions. This position applies deep expertise in advanced analytical tools such as generative AI, machine learning, deep learning, optimization, and statistical modeling to solve complex, high-impact business problems in the healthcare payer domain.
As a Senior II AI Scientist, you will serve as a technical leader and strategic advisor, driving innovation across multiple business areas such as clinical care delivery, customer experience, and payment integrity. This is a hands-on technical leadership role - you will personally architect and build sophisticated AI solutions while simultaneously mentoring junior team members and influencing the technical direction of our AI initiatives. You will lead by example, writing production-quality code, conducting rigorous experiments, and demonstrating best practices in every aspect of AI development. This role requires not only mastery of generative AI, machine learning, and deep learning, but also strong architectural thinking, advanced software engineering capabilities, and the ability to translate ambiguous business challenges into innovative AI solutions.
You will be expected to remain deeply technical, actively contributing code, developing models, and solving complex technical problems alongside your team. Your leadership will come through the quality of your technical work, your ability to tackle the most challenging problems, and your commitment to elevating the skills and capabilities of those around you.
AI Scientists work closely with AI team members in the Product and Engineering tracks to collaboratively develop and deliver models and data-driven products. At the Senior II level, you will lead cross-functional initiatives, establish best practices through your own exemplary work, and serve as a subject matter expert to both technical and business stakeholders - all in service of making our members' health journeys easier.
If you're an accomplished AI Scientist with a proven track record of delivering impactful solutions through hands-on technical excellence and leading others through example in the healthcare industry, apply for this exciting opportunity today!
What You Bring to Cambia:
Qualifications:
The AI Scientist Sr II would have a degree (masters or PhD preferred) in a strongly a strongly quantitative field such as Computer Science, Statistics, Applied Mathematics, Physics, Operations Research, Bioinformatics, or Econometrics, and typically at least 12 years of related work experience. Equivalent combination of education and experience will be considered.
Skills and Attributes:
Technical Leadership & Strategy
  • Recognized expert in generative AI, machine learning, and data science with ability to architect complex, novel solutions and define technical vision aligned with business strategy
  • Deep understanding of the healthcare industry (preferred) with ability to identify and prioritize high-value AI opportunities, evaluate emerging technologies, and lead multiple complex projects from conception to production

Advanced Technical Expertise:
  • Mastery of advanced AI/ML techniques with ability to innovate beyond existing patterns, combined with expert-level Python programming and strong software engineering principles (design patterns, testing, CI/CD)
  • Deep expertise in working with complex, real-world data challenges (noisy, high-dimensional, sparse, imbalanced, biased) across multiple data domains (e.g., claims, clinical, member engagement)
  • Deep expertise in multiple AI modeling techniques with ability to select and combine methods innovatively, design scalable architectures for offline and online systems, and implement MLOps, model governance, and responsible AI practices
  • Advanced SQL and data engineering skills, including optimization of complex queries and data pipeline design

Problem Solving & Innovation:
  • Ability to tackle ambiguous, ill-defined problems and structure them into actionable AI initiatives that create measurable business value
  • Proactive identification of AI opportunities for strategic advantage, with ability to anticipate technical risks, design mitigation strategies, and conduct research and experimentation including A/B testing and causal inference

Leadership & Collaboration:
  • Proven ability to mentor and develop junior AI Scientists while establishing and evangelizing best practices, coding standards, and technical processes
  • Strong leadership presence with ability to influence technical decisions across the organization, lead cross-functional teams, manage stakeholder relationships, and build productive partnerships across departments
  • Excellent communication skills with ability to present complex technical concepts to audiences ranging from technical teams to C-level executives

Business Acumen:
  • Strong ability to translate business strategy into AI opportunities and technical requirements, quantify business impact and ROI of AI initiatives, and balance technical excellence with pragmatic business delivery
  • Understanding of healthcare payer operations, regulations, and industry trends

Core Knowledge:
Generative AI
  • Foundation Models & Architectures: Deep understanding of transformer architectures, attention mechanisms, scaling laws, and experience with multiple model families (GPT, BERT, etc.)
  • Advanced Fine-tuning & Prompt Engineering: Expertise in parameter-efficient fine-tuning (LoRA, QLoRA, Adapters), instruction tuning, domain adaptation, and advanced prompting techniques (chain-of-thought, tree-of-thought, meta-prompting)
  • RAG & Agent Systems: Advanced RAG architectures, hybrid search strategies, knowledge base optimization, and experience designing AI agent systems with tool use, planning, and multi-agent collaboration
  • Evaluation, Alignment & Production: Deep expertise in evaluation methodologies (automated metrics, LLM-as-judge, human evaluation), alignment techniques (RLHF, DPO, constitutional AI), inference optimization, caching strategies, and cost management
  • Multimodal & Responsible AI: Experience with vision-language models and multimodal understanding, plus deep understanding of bias detection and mitigation, hallucination reduction, safety considerations, and privacy-preserving techniques
  • Frameworks & Tools: Expert-level proficiency with Hugging Face ecosystem, LangChain, LlamaIndex, vector databases, and emerging GenAI tools

Machine Learning
  • Advanced Algorithms & Methods: Deep expertise across supervised, unsupervised, semi-supervised, and reinforcement learning paradigms, including ensemble methods (boosting, bagging, stacking), time series forecasting, and causal inference
  • Optimization & Evaluation: Deep understanding of optimization algorithms, convergence properties, custom loss function design, experimental design, statistical testing, and bias-variance tradeoff analysis
  • AutoML & Transfer Learning: Experience with automated model selection, hyperparameter optimization at scale, and advanced techniques for knowledge transfer and few-shot learning

Deep Learning
  • Advanced Architectures & Optimization: Deep understanding of CNNs, RNNs, LSTMs, Transformers, GANs, VAEs, and diffusion models, plus advanced optimization methods, learning rate scheduling, and convergence analysis
  • Regularization & Specialized Domains: Advanced techniques including dropout variants, batch normalization, layer normalization, and architectural regularization, with expertise in NLP, computer vision, or speech processing
  • Model Compression: Knowledge of quantization, pruning, distillation, and efficient inference techniques

Mathematics
  • Core Mathematical Foundations: Advanced linear algebra (matrix decompositions, eigen analysis, numerical methods), probability and statistics (Bayesian methods, hypothesis testing, experimental design), optimization theory (convex optimization, constrained optimization, stochastic optimization), and information theory

Data & Software Engineering
  • Data Architecture & SQL: Understanding of data warehousing, data lakes, modern data stack components, plus advanced SQL including query optimization, window functions, CTEs, and performance tuning
  • Software Engineering & MLOps: Design patterns, testing strategies (unit, integration, end-to-end), version control, CI/CD, model versioning, experiment tracking, model monitoring, and deployment strategies
  • Distributed Computing & Cloud: Experience with distributed training, data parallelism, scalable data processing (Spark, Dask, Ray), and proficiency with cloud AI/ML services (AWS SageMaker, Azure ML, GCP Vertex AI)

What you will do at Cambia:
Note: At the Senior II level, you are expected to demonstrate significant initiative, innovation, and leadership beyond core technical execution. You will shape technical direction, mentor others, and drive strategic AI initiatives.
Technical Leadership & Architecture
  • Lead the design and architecture of complex, multi-component AI systems that solve strategic business problems, while defining technical standards, best practices, and design patterns for AI development across the team
  • Evaluate and recommend new AI technologies, frameworks, and methodologies for adoption, serving as the technical authority on AI/ML topics
  • Drive innovation by researching and prototyping cutting-edge AI techniques applicable to healthcare challenges, and lead technical design reviews to ensure high-quality solutions

Advanced Model Development & Innovation
  • Research, design, and implement novel AI solutions using state-of-the-art generative AI, machine learning, and deep learning techniques to handle complex, real-world healthcare data challenges
  • Design custom algorithms and modeling approaches when existing solutions are insufficient, and develop advanced evaluation frameworks that capture business value and model behavior
  • Create reusable components, libraries, and frameworks that accelerate AI development, and lead the development of production grade AI systems with robust monitoring, governance, and maintenance strategies

Strategic Problem Solving & Business Impact
  • Partner with business leaders to identify high-impact AI opportunities and translate ambiguous business challenges into well-defined AI problems with clear success criteria
  • Design comprehensive experimentation strategies including A/B testing, causal inference, and statistical validation
  • Proactively identify risks, biases, and ethical considerations in AI solutions and develop mitigation strategies, while quantifying and communicating business impact and ROI to executive stakeholders

Data & Engineering Excellence
  • Design and optimize complex data pipelines for model training, evaluation, and serving, while developing advanced feature engineering strategies that unlock model performance
  • Build scalable, maintainable AI systems using modern MLOps practices and cloud infrastructure, with comprehensive monitoring and observability for production systems
  • Ensure data quality, governance, and compliance with healthcare regulations (HIPAA, etc.)

Mentorship & Team Development
  • Mentor junior and mid-level AI Scientists, providing technical guidance and career development support through code reviews and constructive feedback
  • Lead knowledge-sharing sessions, workshops, and technical presentations, while contributing to hiring and onboarding processes
  • Foster a culture of continuous learning, experimentation, and technical excellence

Cross-Functional Collaboration & Communication
  • Lead cross-functional initiatives involving Product, Engineering, and Business stakeholders, communicating complex technical concepts effectively to both technical and non-technical audiences, including executives
  • Build strong partnerships across the organization to identify opportunities and remove blockers, represent the AI team in strategic planning and roadmap discussions, and contribute to thought leadership through presentations, publications, or industry engagement

Responsible AI & Governance
  • Champion responsible AI practices including fairness, transparency, and accountability, while developing frameworks for bias detection, mitigation, and ongoing monitoring
  • Ensure AI solutions comply with regulatory requirements and ethical guidelines, and lead efforts to document model decisions, assumptions, and limitations for governance purposes

Pay ranges vary based on the candidate's work location. The expected hiring range depends on skills, experience, education, and training; relevant licensure / certifications; and performance history.
  • Oregon, Washington, Utah, and Idaho: The expected hiring range is $168,000 - $211,000, the full salary range is $168,000 - $275,000, and the bonus target is 20%.

  • North Dakota: The expected hiring range is $148K - $196K, and the full salary range is $148K - $244K.

About Cambia
Working at Cambia means being part of a purpose-driven, award-winning cul

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