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Explainable Ai Jobs in Virginia (NOW HIRING)

Jobtailor

AI Engineer

Alexandria, VA · On-site

$180 - $240/hr

Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics * Contribute to the integration of AI ...

Dark Wolf Solutions

AI Software Engineer

Chantilly, VA · Remote

$120K - $160K/yr

Implement robust Explainable AI (XAI) techniques to ensure transparency and trustworthiness of model recommendations. * Ensure all AI models, APIs, and data storage solutions strictly adhere to DoD ...

Dark Wolf Solutions

AI Software Engineer

Chantilly, VA · Remote

$120K - $160K/yr

Implement robust Explainable AI (XAI) techniques to ensure transparency and trustworthiness of model recommendations. * Ensure all AI models, APIs, and data storage solutions strictly adhere to DoD ...

Dark Wolf Solutions

AI Software Engineer

Herndon, VA · On-site

$120K - $160K/yr

Implement robust Explainable AI (XAI) techniques to ensure transparency and trustworthiness of model recommendations. * Ensure all AI models, APIs, and data storage solutions strictly adhere to DoD ...

Dark Wolf Solutions, LLC

AI Software Engineer

Herndon, VA · On-site

$120 - $160/hr

Implement robust Explainable AI (XAI) techniques to ensure transparency and trustworthiness of model recommendations. * Ensure all AI models, APIs, and data storage solutions strictly adhere to DoD ...

New

Jobtailor

Senior Data Scientist

Alexandria, VA · On-site

$180 - $260/hr

Apply cutting‑edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics * Work with diverse data types (structured ...

Sunayu

Contingent AI Engineer - Top Secret

Alexandria, VA · On-site

$180 - $240/hr

Apply cutting‑edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics. * Contribute to the integration of AI ...

Jobtailor

Senior Software Engineer

Alexandria, VA · On-site

$180 - $240/hr

Apply cutting‑edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics. * Contribute to the integration of ...

Leidos

Senior AI Engineer

Alexandria, VA · Hybrid

$131K - $237K/yr

Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics. * Contribute to the integration of AI ...

Sierra Nevada Corporation

Sr AI/ML Engineer

Herndon, VA · On-site

$107K - $147K/yr

Familiarity with explainable AI (XAI) techniques for safety-critical environments. * Hands-on experience with reinforcement learning and real-time systems applicable to MPC. Qualifications We Prefer:

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Explainable Ai information

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 are the key skills and qualifications needed to thrive as an Explainable AI specialist?

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 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.

What are popular job titles related to Explainable Ai jobs in Virginia?

For Explainable Ai jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Explainable Ai jobs in Virginia look for?

The top searched job categories for Explainable Ai jobs in Virginia are:

What cities in Virginia are hiring for Explainable Ai jobs?

Cities in Virginia with the most Explainable Ai job openings:

Explainable Ai jobs near you
Infographic showing various Explainable Ai job openings in Virginia as of August 2026, with employment types broken down into 71% Full Time, 27% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

AI Engineer

Jobtailor

Alexandria, VA • On-site

$180 - $240/hr

Other

Posted 5 days ago

Job description

Responsibilities
  • Support the development and operationalization of AI and agentic AI systems in production mission environments
  • Collaborate with multidisciplinary teams of analysts, engineers, and developers to solve complex challenges
  • Deliver innovative, production-ready algorithms and platforms
  • Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics
  • Contribute to the integration of AI, DevSecOps, data engineering, platform engineering, cybersecurity, and observability in a fast‑paced, engineering‑centric environment
Requirements
  • Bachelor’s, Master’s, or equivalent graduate degree in a quantitative or analytical field (Computer Science, Mathematics, Statistics, Engineering, Physics, Computational Social Science, etc.)
  • 12+ years of experience in data science, analytics, or quantitative intelligence analysis
  • Active Top Secret clearance and eligibility for TS/SCI with Polygraph
  • Demonstrated experience collaborating with hybrid teams to research, build, and deploy complex, user‑friendly analytical platforms
  • Experience with AI/ML production engineering, LLMOps/MLOps, RAG architectures, AI orchestration frameworks, Kubernetes‑based AI deployments, OpenAI‑compatible APIs, Python development, GPU inference optimization
Core Competencies

Demonstrates expertise in AI and agentic AI systems development, with a strong foundation in statistical analysis, predictive analytics, and AI/ML production engineering. Proven ability to collaborate with multidisciplinary teams to deliver innovative, user‑friendly analytical platforms in fast‑paced environments.

Highest‑signal resume keywords
  • AI/ML Production Engineering
  • Statistical Analysis
  • Predictive Analytics
  • Python Development
  • Active Top Secret Clearance
Hard Skills
  • Data Science
  • Quantitative Intelligence Analysis
  • Entity Resolution
  • Graph Analytics
  • Explainable AI
  • Operational Analytics
  • Kubernetes‑Based AI Deployments
  • OpenAI‑Compatible APIs
  • GPU Inference Optimization
  • RAG Architectures
Soft Skills
  • Collaboration
  • Problem Solving
  • Innovation
Certifications & Qualifications
  • Bachelor’s Degree
  • Master’s Degree
  • Top Secret Clearance
Industry Keywords
  • AI Systems
  • Agentic AI
  • Analytical Platforms
  • Hybrid Teams
  • Complex Challenges
Tools & Technologies
  • DevSecOps
  • Data Engineering
  • Platform Engineering
  • Cybersecurity
  • Observability
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