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Explainable Ai Jobs in Colorado (NOW HIRING)

Judge Group, Inc.

Principal AI/ML Engineer

Englewood, CO · On-site

$75 - $80.15/hr

Evaluate advancements in transformers, RLHF, generative AI, explainable AI (XAI), edge AI, GPU acceleration, and other cutting-edge technologies. * Drive innovation through research, experimentation ...

Sierra Nevada Corporation

Sr AI/ML Engineer

Longmont, CO

$103K - $141K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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:

Munich Re

Technical Architect - Data, Analytics & AI

Arvada, CO · Hybrid

$65.25 - $84/hr

  • Medical

  • Life

  • Retirement

  • PTO

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...

Sierra Nevada Corporation

Sr AI/ML Engineer

Lone Tree, CO · On-site

$106K - $146K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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:

Sierra Nevada Corporation

Sr AI/ML Engineer

Highlands Ranch, CO · On-site

$102K - $141K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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:

Sierra Nevada Corporation

Sr AI/ML Engineer

Lone Tree, CO

$106K - $146K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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:

Munich Re

Technical Architect - Data, Analytics & AI

Boulder, CO · Hybrid

$67 - $86.25/hr

  • Medical

  • Life

  • Retirement

  • PTO

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...

Munich Re

Technical Architect - Data, Analytics & AI

Aurora, CO · Hybrid

$64.75 - $83.25/hr

  • Medical

  • Life

  • Retirement

  • PTO

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...

Munich Re

Technical Architect - Data, Analytics & AI

Aurora, CO · Hybrid

$65 - $83.50/hr

  • Medical

  • Life

  • Retirement

  • PTO

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...

Munich Re

Technical Architect - Data, Analytics & AI

Lakewood, CO · Hybrid

$64.25 - $82.75/hr

  • Medical

  • Life

  • Retirement

  • PTO

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...

Munich Re

Technical Architect - Data, Analytics & AI

Greeley, CO · Hybrid

$61.25 - $78.75/hr

  • Medical

  • Life

  • Retirement

  • PTO

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...

Munich Re

Technical Architect - Data, Analytics & AI

Arvada, CO · Hybrid

$65 - $83.50/hr

  • Medical

  • Life

  • Retirement

  • PTO

Collaborate with Data Science, Engineering, Security, and Risk teams to enable scalable, secure, and explainable AI solutions . * Establish architectural patterns for AI model deployment, monitoring ...

CDM Smith

Data and AI Governance Lead

Denver, CO · Hybrid

... explainable, and compliant with organization policies. You will collaborate with business ... AI Governance • Partner with the AI Governance Board, AI delivery teams, and platform teams to ...

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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 Colorado?

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

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

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

What cities in Colorado are hiring for Explainable Ai jobs?

Cities in Colorado with the most Explainable Ai job openings:

Explainable Ai jobs near you
Infographic showing various Explainable Ai job openings in Colorado as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, and 3% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution.

Principal AI/ML Engineer

Judge Group, Inc.

Englewood, CO • On-site

$75 - $80.15/hr

Other

Re-posted 10 days ago

Job description

Location: Englewood, CO Salary: $75.00 USD Hourly - $80.15 USD Hourly Description:
Title : Principal AI/ML Engineer
Location: Englewood, CO
Duration: 6 Months Temp to Hire
Pay: $80.15/hr. on W2
Job Summary
We are seeking a highly experienced Principal AI/ML Engineer to lead the technical vision, architecture, and execution of advanced Artificial Intelligence and Machine Learning initiatives. This individual will drive innovation across autonomy, perception, analytics, and generative AI domains while establishing scalable AI/ML frameworks, infrastructure, and best practices.
The ideal candidate combines deep technical expertise with strategic leadership capabilities and has a proven track record of architecting and deploying large-scale, mission-critical AI/ML systems. This role requires the ability to influence technical direction, mentor engineering teams, evaluate emerging technologies, and collaborate with stakeholders to deliver transformative AI-driven solutions.
Key Responsibilities
Technical Leadership & Architecture
  • Define and drive long-term AI/ML strategy, technical roadmaps, and architectural standards.
  • Lead the design and development of advanced AI solutions including deep learning, reinforcement learning, multimodal generative AI, perception systems, and decision-making algorithms.
  • Architect scalable end-to-end AI/ML systems across cloud, enterprise, edge, and embedded environments.
  • Translate high-level business and mission objectives into actionable AI/ML architectures, technical frameworks, data strategies, and resource plans.
  • Guide engineering trade studies, technology selection, and system-level design decisions.

AI/ML Platform & Infrastructure
  • Define and advocate for scalable AI/ML infrastructure, including data pipelines, compute environments, MLOps platforms, cloud/on-premise systems, and deployment frameworks.
  • Establish best practices for the complete AI/ML lifecycle, including:
    • Data management and governance
    • Model development and versioning
    • CI/CD for machine learning
    • Monitoring and performance tracking
    • Validation and continuous improvement
  • Ensure AI/ML solutions are designed for scalability, reliability, security, and enterprise-wide adoption.

Research & Innovation
  • Identify and champion emerging AI/ML technologies and high-value R&D opportunities.
  • Evaluate advancements in transformers, RLHF, generative AI, explainable AI (XAI), edge AI, GPU acceleration, and other cutting-edge technologies.
  • Drive innovation through research, experimentation, prototyping, and technology demonstrations.
  • Develop reusable frameworks, accelerators, and common assets that support multiple programs and initiatives.

Program Execution & Collaboration
  • Oversee multiple AI/ML development efforts simultaneously, conducting technical reviews, risk assessments, and mitigation planning.
  • Collaborate with engineering, product, infrastructure, and leadership teams to align AI/ML initiatives with organizational goals.
  • Lead the development of simulation environments, sensor fusion models, computer vision systems, and autonomy solutions.
  • Present technical concepts, demonstrations, and strategic recommendations to executive leadership and stakeholders.

Mentorship & Team Development
  • Provide technical leadership and guidance to engineering teams.
  • Mentor engineers and data scientists, fostering technical excellence and professional growth.
  • Help define staffing requirements, resource planning, and skill development strategies.
  • Promote a culture of innovation, collaboration, and continuous learning.

Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related STEM field.
  • 14+ years of experience in AI/ML, machine learning engineering, data science, or related technical disciplines.
  • Deep expertise in:
    • AI/ML system architecture
    • Deep learning
    • Reinforcement learning
    • Generative AI and foundation models
    • Large-scale machine learning systems
  • Strong programming skills in one or more of the following:
    • Python
    • C++
    • C#
    • Java
  • Proven experience architecting, deploying, and scaling complex AI/ML systems in production environments.
  • Demonstrated experience providing technical leadership across programs, teams, or organizations.
  • Experience defining technical strategy and influencing senior stakeholders.
  • Strong understanding of cybersecurity, system reliability, and compliance considerations in AI/ML environments.
  • Proven ability to mentor and develop engineering talent.

Preferred Qualifications
  • Master's degree or PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related field.
  • Experience applying AI/ML to:
    • Autonomous systems
    • Sensor fusion
    • Computer vision
    • Embedded or real-time platforms
  • Expertise with:
    • MLOps platforms and ML engineering standards
    • Validation and verification frameworks
    • Data management and governance
    • GPU acceleration technologies
    • CUDA and TensorRT
    • Parallel and distributed computing
  • Knowledge of:
    • Edge AI
    • Explainable AI (XAI)
    • Emerging AI/ML technologies
    • Human-machine interaction (HMI) systems
    • Autonomy architectures and decision systems
  • Publications, patents, conference presentations, or recognized thought leadership in AI/ML.

Technical Skills
Required
  • AI/ML System Architecture
  • Deep Learning
  • Reinforcement Learning
  • Generative AI / Generative Models
  • Python
  • Scalable Machine Learning Systems
  • Technical Leadership

Preferred
  • TensorRT
  • CUDA
  • C++
  • C#
  • Java
  • MLOps
  • Data Management
  • Validation Frameworks
  • GPU Acceleration
  • Parallel Computing
  • Edge AI
  • Explainable AI (XAI)
  • Multimodal Sensor Fusion
  • Embedded Systems
  • Real-Time AI Applications
  • Advanced AI Research & Innovation

Ideal Candidate
The ideal candidate is a visionary AI/ML leader who can combine strategic thinking, hands-on technical expertise, and organizational influence to deliver innovative AI solutions at scale. They are passionate about emerging technologies, capable of solving highly complex problems, and committed to building high-performing technical teams while advancing next-generation AI capabilities.
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