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$11K

$102.9K

$133K

How much do artificial intelligence explainable jobs pay per year?

As of Sep 8, 2026, the average yearly pay for artificial intelligence explainable in the United States is $102,938.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $132,500.00 per year, depending on experience, location, and employer.

What is artificial intelligence explainable?

Artificial Intelligence Explainables, often referred to as Explainable AI (XAI), are methods and techniques that make the results and processes of AI systems understandable to humans. XAI helps users and stakeholders comprehend how AI models make their decisions, increasing trust and transparency. This is especially important in critical fields like healthcare, finance, and law, where understanding AI reasoning can impact lives or regulations. By providing clear explanations, XAI also helps developers identify potential biases or errors in AI models.

What are the key skills and qualifications needed to thrive as an artificial intelligence explainability specialist?

To thrive as an Artificial Intelligence Explainability Specialist, you need a strong background in machine learning, statistics, and data science, typically supported by a degree in computer science or a related field. Familiarity with explainability frameworks (such as LIME, SHAP, or Fairness Indicators), programming languages like Python, and cloud-based AI platforms is essential. Critical thinking, clear communication, and the ability to translate complex technical concepts to non-technical stakeholders are standout soft skills. These skills ensure that AI models are transparent, trustworthy, and can be effectively adopted in real-world applications where accountability and compliance are crucial.

What are some common challenges faced by professionals working in artificial intelligence explainability, and how can they be addressed?

Professionals in Artificial Intelligence Explainability often encounter challenges such as translating complex AI model decisions into transparent, user-friendly explanations and ensuring those explanations are understandable to non-technical stakeholders. Additionally, balancing the trade-off between model accuracy and interpretability can be difficult, as more interpretable models sometimes sacrifice predictive performance. To address these challenges, practitioners typically use a combination of model-agnostic explainability tools, collaborate closely with data scientists and domain experts, and prioritize clear communication with end users. Ongoing learning and staying up-to-date with the latest research in explainable AI also help in overcoming these hurdles.

What is the difference between Artificial Intelligence Explainable vs Data Scientist?

AspectArtificial Intelligence ExplainableData Scientist
Required CredentialsTypically requires knowledge of AI, machine learning, and data analysis; certifications in AI or data science are commonRequires degrees in computer science, statistics, or related fields; certifications in data analysis or machine learning are beneficial
Work EnvironmentOften works in AI development teams, research labs, or tech companies focusing on explainability of AI modelsWorks in data analysis, modeling, and insights generation across various industries like finance, healthcare, and tech
Industry UsageUsed in AI model development, especially for transparent and interpretable AI systemsApplied in data analysis, predictive modeling, and business intelligence

In summary, Artificial Intelligence Explainable specialists focus on making AI models transparent and understandable, often working closely with AI development teams. Data Scientists analyze data and build models but may not specialize in explainability. Both roles require strong analytical skills and knowledge of machine learning, but their primary focus and work environments differ.

What other helpful pages are available for Artificial Intelligence Explainable?

Other pages related to Artificial Intelligence Explainable:

Infographic showing various Artificial Intelligence Explainable job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $102,938 per year, or $49.5 per hour.

Senior Artificial Intelligence Associate//Dearborn, MI//W2 only

Dearborn, MI • On-site

Saanvi Technologies
51 - 200 employees
Learn more about Saanvi Technologiesexternal

Contractor

Re-posted 11 days ago

Job description

Senior Artificial Intelligence Associate

Dearborn, MI 4days onsite

W2

Position Description:

Employees in this job function are responsible for developing intelligent programs, cognitive applications and algorithms for data analysis and automation, leveraging various AI techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming Key Responsibilities: 1) Understand business requirements and develop AI algorithms, models and programs to solve complex problems, generate recommendations, extract patterns, make predictions, interpret sensor data (images, sound), orchestrate automation and enable self-service capabilities 2) Perform large-scale experimentation and develop data driven applications that translate data into actionable intelligence 3) Drive innovative applications of Artificial Intelligence tools and techniques such as deep learning, generative AI, natural language processing, image processing, cognitive automation, intelligent process automation, reinforcement learning, virtual assistants and specialized programming 4) Research and optimize AI technologies to enhance efficiency and accuracy of data analysis and create more efficient automation

Skills Required:

Google Cloud Platform, Python

Skills Preferred:

This role focuses on hands-on development of AI-powered systems that: • Integrate Google LLMs with BigQuery data • Build tool-using AI agents for root cause analysis • Persist investigation intelligence across sessions • Deliver explainable insights to quality engineers What You Will Buil d • AI agents that generate and execute BigQuery SQL autonomously • Investigation memory models (structured + optional semantic) • Multi-step reasoning workflows • APIs that power UX for quality engineers • Logging, traceability, and governance mechanisms

Experience Required:

Senior Associate Exp: 3 to 5 years experience in relevant field

Experience Preferred:

•Experience with Infrastructure-as-Code (Terraform) and DevOps practices. •Familiarity with CI/CD tools like Tekton or Jenkins. •Experience with Cloud Run, Big Query and GitHub CoPilot. •Understanding of Agile methodologies. •Experience with backend frameworks such as Flask, Django, FastAPI. •Experience with Test-First/Test Driven Development (TDD), MVP, Evolutionary design. •Basic understanding of Machine Learning.

Education Required:

Bachelor's Degree

Education Preferred:

Additional Safety Training/Licensing/Personal Protection Requirements:

Additional Information :

4 days on site

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About Saanvi Technologies

Sourced by ZipRecruiter

Saanvi Technologies is a staffing company that specializes in providing IT professionals to businesses. Our employees are experts in their field, and have the skills and experience necessary to help businesses grow and succeed. Saanvi Technologies is dedicated to helping businesses achieve their goals, and they have a proven track record of success. Our employees are qualified and reliable, and they always go above and beyond to meet the needs of their customers.

Company size

51 - 200 Employees

Headquarters location

Farmington, MI, US

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