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Ai Model Jobs in Oregon (NOW HIRING)

Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required -- your domain knowledge is what matters. Scope of Work

Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required -- your domain knowledge is what matters. Scope of Work

Data Modeling, Data Integration, Analytics and AI lifecycle management * Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives ...

Data Modeling, Data Integration, Analytics and AI lifecycle management * Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives ...

Data Modeling, Data Integration, Analytics and AI lifecycle management * Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives ...

Vice President, Engineering and AI Innovations

OR · On-site +1

$179K - $231K/yr

Familiarity with model evaluation, A/B testing, safety techniques, latency/throughput trade-offs, and observability for AI systems. * Understanding of fine-tuning, distillation, and model ...

Develop and deploy Large Language Model (LLM) and Generative AI applications that improve engineering productivity, accelerate troubleshooting, and enhance knowledge discovery. * Analyze large-scale ...

Be Seen First

Develop and refine AI models to meet product and research needs * Tune performance of models to ensure accuracy and efficiency * Conduct research to stay on the cutting edge of AI technology * Test ...

Showing results 41-60

Ai Model information

What is an AI model?

AI models are computer programs designed to simulate human intelligence by learning patterns from data and making predictions or decisions based on that learning. These models can perform a variety of tasks, such as recognizing speech, translating languages, analyzing images, and generating text. AI models are created using machine learning algorithms and are trained on large datasets to improve their accuracy and performance. Popular examples include neural networks, decision trees, and support vector machines. The effectiveness of an AI model depends on the quality of the data, the chosen algorithm, and the training process.

What are the key skills and qualifications needed to thrive as an AI model, and why are they important?

To excel as an AI Model Developer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and typically a degree in computer science, data science, or a related field. Familiarity with ML frameworks like TensorFlow or PyTorch, cloud platforms, and relevant certifications such as TensorFlow Developer or AWS Machine Learning Specialty are valuable. Critical thinking, continuous learning, and effective collaboration with interdisciplinary teams are key soft skills for success. These competencies enable the creation of accurate, reliable AI models that can effectively solve complex real-world problems.

What are some common challenges faced by professionals working as AI model developers, and how can they address them?

Professionals working as AI Model developers often encounter challenges such as managing large and complex datasets, ensuring model accuracy, and addressing issues of bias in algorithms. They may also need to balance the trade-off between model performance and interpretability, especially when deploying models in production environments. To overcome these challenges, AI Model developers typically collaborate closely with data engineers, domain experts, and other stakeholders, regularly validate their models, and stay updated with the latest advancements in the field to adopt best practices.

What is the difference between Ai Model vs Data Scientist?

AspectAi ModelData Scientist
Required CredentialsKnowledge of machine learning, programming skills, sometimes certifications in AI/MLDegree in data science, statistics, computer science; certifications beneficial
Work EnvironmentFocus on developing, training, and deploying AI modelsData analysis, interpretation, and visualization; often collaborates with AI teams
Industry UsageUsed in AI development, automation, and predictive modelingApplied across industries for insights, reporting, and decision-making

While both roles involve working with data and algorithms, an Ai Model primarily focuses on creating and refining AI systems, whereas a Data Scientist analyzes data to generate insights and supports AI development. The roles often overlap but serve distinct functions within the data and AI ecosystem.

What is the easiest AI Model job to get into?

Entry-level AI model jobs often include roles such as data annotator or junior machine learning assistant, which typically require basic programming skills in Python and understanding of data labeling. These positions usually have lower experience requirements and may offer on-the-job training, making them accessible for beginners entering the AI field.

What are popular job titles related to Ai Model jobs in Oregon?

For Ai Model jobs in Oregon, the most frequently searched job titles are:

What cities in Oregon are hiring for Ai Model jobs?

Cities in Oregon with the most Ai Model job openings:

Infographic showing various Ai Model job openings in Oregon as of August 2026, with employment types broken down into 65% Full Time, 21% Part Time, and 14% Contract. Highlights an 93% In-person, and 7% Remote job distribution.

AI Training Specialist - Life Sciences

micro1 AI

Salem, OR • Remote

$90 - $120/hr

Part-time

This job post has expired today. Applications are no longer accepted.


Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.