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Ai Integration Jobs in Oregon (NOW HIRING)

Arize AI

Senior AI Product Manager, Observability

OR · On-site +1

$200K - $250K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Whether it's developing the next generation of human-level intelligence, enhancing voice assistants, or enabling researchers to analyze genetic markers at scale, AI is increasingly integrated into ...

Les Schwab Tire Centers

Sr Integration Engineer

Bend, OR · On-site

$120 - $150/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Design, develop, and implement data solutions with integration platform tools, cloud hosting, event management, AI platforms, and API gateways. * Collaborate with business partners, translate ...

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Showing results 21-40

All JobsAi Integration JobsAi Integration Jobs in Oregon

Ai Integration information

See Oregon salary details

$22.7K

$124.7K

$180.8K

How much do ai integration jobs pay per year?

As of Aug 18, 2026, the average yearly pay for ai integration in Oregon is $124,745.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,200.00 and $154,900.00 per year, depending on experience, location, and employer.

What is AI integration?

AI integration refers to the process of incorporating artificial intelligence technologies into existing systems, applications, or business processes to enhance automation, improve decision-making, and optimize performance. This can involve connecting AI models, such as machine learning algorithms or natural language processing tools, with software platforms, databases, or workflows. The goal is to enable systems to analyze data, learn from patterns, and perform tasks that traditionally required human intelligence. AI integration can benefit a wide range of industries, including healthcare, finance, manufacturing, and customer service.

What are some common challenges faced when integrating AI solutions into existing business processes?

One of the most common challenges in AI integration is ensuring that new AI tools seamlessly interact with legacy systems and data formats. Team members often need to address data quality issues, adapt workflows, and manage stakeholder expectations regarding the capabilities and limitations of AI. Collaboration with IT, operations, and business units is essential to customize solutions and ensure user adoption. Additionally, ongoing monitoring and retraining of AI models is necessary to maintain performance and align with evolving business goals.

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

To excel as an AI Integration Specialist, you need a solid background in computer science, proficiency in programming languages (such as Python), and experience with machine learning frameworks, often supported by a relevant degree or certifications. Familiarity with cloud platforms (like AWS, Azure, or Google Cloud), APIs, and integration tools is typically required. Strong problem-solving skills, effective communication, and the ability to collaborate across teams make someone stand out in this role. These competencies are crucial for successfully implementing AI solutions that align with business needs and ensuring seamless system interoperability.

What is the difference between Ai Integration vs Data Analyst?

AspectAi IntegrationData Analyst
Required CredentialsBachelor's in Computer Science, Engineering, or related fields; knowledge of AI/ML toolsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentTech companies, AI development teams, software firmsBusiness, finance, healthcare, and other industries analyzing data
Employer & Industry UsageDeveloping AI solutions, integrating AI into productsInterpreting data, generating reports, supporting decision-making

While Ai Integration specialists focus on implementing AI systems and integrating AI technologies into applications, Data Analysts interpret data to provide insights and support business decisions. Both roles require analytical skills, but Ai Integration emphasizes technical development and system integration, whereas Data Analysts focus on data interpretation and reporting.

How to get into AI integration?

To pursue a career in AI integration, develop skills in programming languages like Python, understand machine learning frameworks, and gain experience with AI tools and APIs. Earning relevant certifications and working on projects that demonstrate AI implementation can improve job prospects.

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

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

What job categories do people searching Ai Integration jobs in Oregon look for?

The top searched job categories for Ai Integration jobs in Oregon are:

What cities in Oregon are hiring for Ai Integration jobs?

Cities in Oregon with the most Ai Integration job openings:

Ai Integration jobs near you
Infographic showing various Ai Integration job openings in Oregon as of August 2026, with employment types broken down into 75% Full Time, 23% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution, with an average salary of $124,745 per year, or $60 per hour.

AI Training Specialist - Cheminformatics

micro1 AI

Beaverton, OR • Remote

$80 - $110/hr

Part-time

Posted 15 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery 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 and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

Apply