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Explainable Ai Jobs (NOW HIRING)

Purple Drive Technologies

Gen AI architect

Mclean, VA · On-site

$63.75 - $84/hr

Implement Responsible AI strategies, ensuring ethical, compliant, and explainable AI solutions. * Collaborate with engineering, product, and data teams to translate business problems into AI-driven ...

Ai Square

Technical Writer

Manhattan, NY · On-site

AI Research Scientist Location: San Francisco, USA Lead groundbreaking research in AI, focusing on federated learning, explainable AI, and applied industrial solutions. Develop and publish research ...

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How much do explainable ai jobs pay per year?

As of Jun 5, 2026, the average yearly pay for explainable ai in the United States is $112,009.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,500.00 and $127,000.00 per year, depending on experience, location, and employer.

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

To thrive as an Explainable AI specialist, you need a strong background in machine learning, data science, and statistics, typically with an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and libraries like LIME or SHAP, as well as experience in model interpretability tools, is essential. Strong analytical thinking, effective communication, and the ability to translate complex technical concepts for non-technical stakeholders are crucial soft skills. These capabilities ensure that AI models are transparent, trustworthy, and can be responsibly integrated into decision-making processes.

What are some of the typical challenges faced when working in Explainable AI and how do professionals address them?

Professionals in Explainable AI often encounter challenges such as balancing model accuracy with interpretability, translating complex model outputs into understandable insights for non-technical stakeholders, and ensuring transparency without compromising sensitive data. Addressing these issues typically involves using specialized tools and frameworks for visualization, collaborating closely with data scientists, domain experts, and business teams, and staying updated on the latest research in model interpretability. Continuous learning and open communication are key to overcoming these challenges and delivering AI solutions that are both effective and trustworthy.

What is Explainable AI?

Explainable AI (XAI) refers to methods and techniques in artificial intelligence that make the results of AI models understandable and interpretable by humans. XAI aims to provide transparency into how AI systems make decisions, helping users trust and effectively manage AI applications. This is especially important in fields like healthcare, finance, and law, where understanding the reasoning behind AI-driven outcomes can be crucial for accountability and compliance. By making AI more transparent, XAI also helps identify and address biases or errors in AI systems.

What is the difference between Explainable Ai vs Data Scientist?

AspectExplainable AiData Scientist
CredentialsTypically requires knowledge of AI, machine learning, and data analysis; certifications like AI or ML courses are commonRequires degrees in computer science, statistics, or related fields; certifications in data analysis or machine learning are beneficial
Work EnvironmentWorks within AI development teams, focusing on model transparency and interpretabilityWorks across data analysis, model building, and business insights, often in research or corporate settings
Industry UsageUsed in AI development, healthcare, finance, and any field requiring transparent AI modelsApplied in tech, finance, healthcare, and research for data-driven decision making

Explainable Ai focuses on making AI models transparent and understandable, ensuring trust and compliance. Data Scientists develop and analyze models, often working with complex data. While both roles involve AI and data, Explainable Ai specialists emphasize interpretability, whereas Data Scientists focus on model creation and insights.

More about Explainable Ai jobs
What cities are hiring for Explainable Ai jobs? Cities with the most Explainable Ai job openings:
What states have the most Explainable Ai jobs? States with the most job openings for Explainable Ai jobs include:
What job categories do people searching Explainable Ai jobs look for? The top searched job categories for Explainable Ai jobs are:
Explainable Ai jobs near you
Infographic showing various Explainable Ai job openings in the United States as of May 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 77% Physical, 4% Hybrid, and 19% Remote job distribution, with an average salary of $112,009 per year, or $53.9 per hour.
Research Assistant-AI Driven Disaster and Emergency Management System

Research Assistant-AI Driven Disaster and Emergency Management System

Angelo State University

San Angelo, TX • On-site

$15 - $20/hr

Full-time

Posted 18 days ago

Angelo State University rating

6.0

Company rating: 6.0 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

481st of 532 rated colleges and universities

Job description

Position Details Position Information Job Title Research Assistant-AI Driven Disaster and Emergency Management System Position Type Student Division Academic Affairs Department Computer Science Job Description Computer Science is seeking highly motivated undergraduate or graduate research assistants (GRA) to contribute to a cutting-edge, interdisciplinary research project focused on developing an AI-enabled, secure, and interoperable disaster and emergency management platform. The project addresses critical challenges observed in large-scale disasters-such as delayed alerts, lack of coordination among agencies, and limited use of intelligent decision-support systems-by integrating knowledge graphs, explainable AI (XAI), real-time alerting, LLM-based interaction, and cybersecurity/privacy mechanisms. Key Responsibilities
  • Collect, preprocess, and manage heterogeneous data from sensors, system logs, policy documents, and open-source disaster datasets.
  • Design and implement a unifi ed knowledge graph-based data model for data integration and interoperability.
  • Develop and evaluate AI/ML models tailored to diff erent stakeholders (e.g., fi rst responders, government agencies, researchers).
  • Integrate Explainable AI (XAI) techniques to provide transparent and interpretable decision support.
  • Contribute to the development of a real-time smart alert and communication system.
  • Assist in building an LLM-based conversational interface for natural language interaction with the platform.
  • Implement and evaluate security and privacy mechanisms for secure data sharing and system access.
  • Participate in system testing using the TEEX Disaster City testbed and other benchmark datasets.
  • Contribute to technical reports, research papers, presentations, and proposal development.
Required Qualifications
  • Must be a currently enrolled student, registered for classes, in an undergraduate or graduate program in Computer Science, AI, Cybersecurity, Data Science, or a closely related field.
  • Strong programming skills in Python.
  • Knowledge of machine learning or deep learning.
  • Familiarity with data structures, databases, and basic software development practices.
  • Ability to work both independently and collaboratively in a research environment.
Preferred Qualifications
  • Experience with knowledge graphs, graph databases, or semantic web technologies (e.g., RDF, SPARQL, Neo4j).
  • Background in natural language processing, LLMs, or information extraction.
  • Familiarity with XAI, cybersecurity, privacy-preserving methods, or distributed systems.
  • Experience with cloud platforms, real-time data processing, or IoT data.
  • Prior research experience and interest in publishing.
Physical Demands Salary $15-$20/hour EEO Statement All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, genetic information, or status as a protected veteran. In compliance with the Americans with Disabilities Act (ADA), Angelo State University is committed to providing reasonable accommodations to ensure equal access to employment opportunities for qualified individuals with disabilities. We are committed to ensuring that a qualified individual with a disability has the same rights and privileges in employment as non-disabled employees. If an accommodation is requested for the job application process, please contact our office at (325) 942-2168 or email us at hr@angelo.edu. Posting Detail Information Posting Number Number of Vacancies 1 Open Date 03/18/2026 Close Date Open Until Filled Yes Special Instructions to Applicant In the "Other" application documents needed: * Statement of research interest *(Optional) Links to GitHub, publications, or prior projects Questions: Dr. Erdogan Dogdu (erdogan.dogdu@angelo.edu)

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