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Applied Ai Engineer Jobs in Colorado (NOW HIRING)

Lead AI Engineer

Denver, CO · On-site

$147K - $202K/yr

Building blocks for success Required: * 6+ years of experience in software engineering, platform engineering, data engineering, applied AI, automation, technology consulting, or a related technical ...

Lead AI Engineer

Denver, CO · On-site

$147K - $202K/yr

Building blocks for success Required: * 6+ years of experience in software engineering, platform engineering, data engineering, applied AI, automation, technology consulting, or a related technical ...

AI Engineer

Denver, CO · On-site +1

$100K - $135K/yr

Data Engineering Employment Type: Permanent - Full Time Location: Remote USA - In Tandem ... What you bring: * 5+ years shipping production software, including meaningful applied AI or ML work.

AI Engineering Lead

Denver, CO · On-site

$147 - $220/hr

Role Summary We are hiring a founding AI Engineer Lead to build and scale AI capabilities from the ... Help establish engineering standards and best practices for applied AI across the organization

The Applied AI / AWS Engineer II resolves bottlenecks in testing workflows by engineering automated utilities and integrating Generative and Agentic AI into software delivery practices. Operating ...

AI Engineering Lead

Denver, CO · On-site +1

$105K - $139K/yr

We are hiring a founding AI Engineer Lead to build and scale AI capabilities from the ground up ... applied AI across the organization • Establish reusable components, frameworks, and templates to ...

Join our mission to infuse cutting-edge AI/ML/GenAI into healthcare as a Staff Applied AI/ML ... Collaborate with product managers, engineers, and other stakeholders as a specialist and subject ...

Collaborate with product managers, engineers, and other stakeholders as a specialist and subject ... Minimum 8 years of experience in industry with a strong focus on applied AI/ML research and ...

Senior Applied AI/ML Scientist

Denver, CO · On-site

$180K - $225K/yr

Join our mission to infuse cutting-edge AI/ML/GenAI into healthcare as a Senior Applied AI/ML ... engineering, model training, validation, and deployment. * Participate in code reviews, testing ...

Senior Cloud & AI Engineer

Denver, CO · On-site

$107K - $147K/yr

You will work at the intersection of cloud infrastructure, platform engineering, and applied AI - evaluating where agentic automation can replace manual toil, where deterministic automation is the ...

Senior Cloud & AI Engineer

Denver, CO · On-site

$107K - $147K/yr

You will work at the intersection of cloud infrastructure, platform engineering, and applied AI - evaluating where agentic automation can replace manual toil, where deterministic automation is the ...

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Showing results 1-20

Applied Ai Engineer information

What are the key skills and qualifications needed to thrive as an applied AI engineer?

To thrive as an Applied AI Engineer, you need strong proficiency in programming (especially Python), machine learning algorithms, statistics, and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of data management tools are typically required. Excellent problem-solving, communication, and teamwork skills help you translate complex models into real-world solutions and collaborate across disciplines. These competencies ensure you can effectively develop, deploy, and maintain AI systems that drive business value.

What are some common challenges applied AI engineers face when deploying AI models into production environments?

Applied AI Engineers often encounter challenges such as ensuring models perform consistently on real-world data, optimizing models for speed and scalability, and integrating AI solutions with existing systems. Managing data privacy, monitoring for model drift, and maintaining robust documentation are also key concerns. Collaboration with DevOps, data engineering, and product teams is essential to address these challenges effectively and deliver reliable AI-driven solutions.

What is the difference between Applied Ai Engineer vs Data Scientist?

AspectApplied Ai EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys AI models in production environmentsAnalyzes data to extract insights and build predictive models
Industry UsageUsed in tech, healthcare, finance for deploying AI solutionsUsed across industries for data analysis and modeling

Applied Ai Engineers focus on implementing and deploying AI models in real-world applications, while Data Scientists primarily analyze data to generate insights and build predictive models. Both roles require similar educational backgrounds but differ in their core responsibilities and work environments.

How much does an applied AI engineer make?

An applied AI engineer's salary varies based on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually. Senior roles or those with specialized skills in machine learning, deep learning, and programming languages like Python or TensorFlow tend to earn higher salaries.

What does an applied AI engineer do?

An applied AI engineer develops and implements artificial intelligence models and algorithms to solve real-world problems. They work with data, machine learning frameworks, and programming languages like Python or TensorFlow to create practical AI solutions for businesses or products.

What are popular job titles related to Applied Ai Engineer jobs in Colorado?

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

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

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

What cities in Colorado are hiring for Applied Ai Engineer jobs?

Cities in Colorado with the most Applied Ai Engineer job openings:

Infographic showing various Applied Ai Engineer job openings in Colorado as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 70% Physical, 3% Hybrid, and 27% Remote job distribution.

Director of Applied AI & ML Engineering

Denver, CO • On-site

Full-time

Re-posted 11 days ago


Job description

Paradigm is a software company transforming the way that the residential construction & building product industries operate across the globe. We are looking for a Director, Applied AI & ML Engineering to be part of revolutionizing these industries.

The Director, Applied AI & ML Engineering will lead the strategy, architecture, and deployment of intelligent systems that transform how homes are designed, estimated, and built. This role will drive the integration of AI and machine learning across the residential construction lifecycle—from digital plan understanding and takeoffs to automated estimating, material optimization, and design personalization.

The ideal leader blends technical depth with strategic clarity—able to guide teams across computer vision, large language models, and agentic automation while ensuring reliable, scalable delivery within the construction domain.

What You Will Do:

  • Define and lead the Applied AI & ML strategy for residential construction, identifying and prioritizing use cases that enhance speed, accuracy, and efficiency.

  • Build and maintain a roadmap of agentic AI systems that automate key construction workflows—such as plan interpretation, quantity takeoffs, cost estimation, and material specification optimization, while enabling seamless integration with suppliers, ERP platforms, and technology providers.

  • Partner with Product, Engineering, and Operations leaders to embed AI capabilities into core platforms and customer-facing applications.

  • Lead the design of AI-powered and multi-agent systems that connect workflows across design, estimating, procurement, and field execution.

  • Architect retrieval-augmented generation (RAG) and computer vision pipelines that interpret plan sets, generate takeoffs, and surface contextual insights.

  • Combine LLMs, CV, and rule-based logic to deliver explainable and auditable systems tailored to construction professionals.

  • Ensure architectural scalability, performance, and observability in all deployed systems.

  • Oversee the end-to-end ML lifecycle—from experimentation and model development to deployment, monitoring, and iteration.

  • Implement best practices in MLOps, data management, and continuous delivery pipelines.

  • Deliver measurable improvements in model quality, reasoning accuracy, and cost efficiency through advanced evaluation methods, such as Evals, zero- and few-shot benchmarking, Chain-of-Thought, and LLM-as-a-judge techniques to guide continuous model refinement.

  • Build, mentor, and lead a cross-functional team of applied AI and ML engineers, partnering closely with product, design, and software engineering teams to deliver production-grade AI-powered systems.

  • Foster a culture of collaboration, experimentation, and responsible AI development.

  • Manage vendor relationships and technology partnerships across cloud and AI platforms.

  • Collaborate with design, estimating, and operations teams to identify automation opportunities and ensure successful adoption.

  • Translate complex AI concepts into clear direction for business and product stakeholders.

  • Represent the organization’s AI vision in external partnerships, technical forums, and industry collaborations.

What You Need to Succeed:

  • 12+ years of experience in applied AI, ML, and/or Software engineering, with at least 5 years in a leadership role.

  • Bachelor’s or advanced degree in Computer Science, Machine Learning, or a related field preferred.

  • Proven success designing and deploying AI-driven systems in production environments.

  • Expertise in LLMs, computer vision, multimodal models, and retrieval-augmented generation (RAG) architectures.

  • Strong foundation in modern software engineering—including APIs, microservices, CI/CD, and containerization.

  • Hands-on familiarity with ML platforms such as MLflow, Kubeflow, or SageMaker for model training and deployment.

  • Demonstrated ability to collaborate across engineering, product, and operations in a complex technical environment.

  • Excellent written and verbal communication skills for both technical and executive audiences.

  • Experience in residential construction technology, including estimating, takeoffs, or design automation is preferred.

  • Background in BIM/CAD integration, digital twin platforms, or 3D modeling workflows is preferred.

  • Familiarity with agent orchestration frameworks (Temporal, n8n, LangGraph) and enterprise API integration is preferred.

  • Understanding of AI governance, auditability, and human-in-the-loop validation frameworks is preferred.

  • Experience with Azure, AWS, or GCP cloud platforms for scalable AI deployment is preferred.

Ready to Join? Apply now! MyParadigm.com/careers/
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