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Data Engineer Ml Jobs in Iowa (NOW HIRING)

AI Practitioner

West Des Moines, IA ยท On-site

$125 - $150/hr

... Data Science, Artificial Intelligence, Engineering, or a related field (Master's preferred but not required). Experience * 2-5 years of experience developing and implementing AI/ML solutions in an ...

... Science, Data Science, Artificial Intelligence, Engineering, or a related field (Master's preferred but not required). Experience ยท 2-5 years of experience developing and implementing AI/ML ...

Data Architect

Cedar Rapids, IA ยท On-site

$62.75 - $80.75/hr

... with DevOps, Engineering, Analytics, Data Governance, and other cross-functional teams to ... cloud, AI/ML, and emerging technologies. โ€ข Effective facilitation and consensus-building ...

Responsibilities : โ€ข Define and drive the organization's AI roadmap, architecture, and long-term technical vision. โ€ข Lead and mentor AI/ML engineers, data scientists, and cross-functional teams ...

Solve complex problems while ensuring protection of data, models, and systems. Hands-On AI Security Engineering Actively contribute to architecture, design, and development of AI/ML and GenAI systems ...

Solve complex problems while ensuring protection of data, models, and systems. Hands-On AI Security Engineering Actively contribute to architecture, design, and development of AI/ML and GenAI systems ...

Required Skills 7+ years of technical leadership with data or platform engineering roles preferred Experience or deep understanding of designing or enabling federated data/ML environments where teams ...

Computer Engineering * Strong technical skills in the following areas: * Proficiency in Python ... Exposure to AI/ML concepts (e.g., regression, classification, clustering, NLP, generative AI/LLMs)

Computer Engineering * Strong technical skills in the following areas: * Proficiency in Python ... Exposure to AI/ML concepts (e.g., regression, classification, clustering, NLP, generative AI/LLMs)

Computer Engineering * Strong technical skills in the following areas: * Proficiency in Python ... Exposure to AI/ML concepts (e.g., regression, classification, clustering, NLP, generative AI/LLMs)

Showing results 21-40

Data Engineer Ml information

What does a data engineer ML do?

A Data Engineer ML (Machine Learning) is responsible for designing, building, and maintaining the data pipelines and infrastructure necessary for machine learning applications. They clean, process, and organize large datasets to ensure data quality and accessibility for data scientists and ML engineers. In addition, they may work on deploying machine learning models to production environments and optimizing data workflows for efficiency and scalability.

What are the key skills and qualifications needed to thrive as a data engineer ML?

To thrive as a Data Engineer ML, you need strong programming skills (especially in Python or Scala), knowledge of data modeling, and a solid foundation in database technologies, typically supported by a degree in computer science or a related field. Familiarity with big data frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and ETL tools, as well as relevant certifications, is highly beneficial. Excellent problem-solving abilities, teamwork, and clear communication help you collaborate with data scientists and stakeholders effectively. These skills are essential for building robust data pipelines and infrastructure that enable scalable, high-quality machine learning solutions.

How do data engineer ML roles typically collaborate with data scientists and machine learning engineers on projects?

Data Engineer ML professionals work closely with data scientists and machine learning engineers by building and maintaining robust data pipelines, ensuring clean and reliable datasets are readily available for modeling and analysis. They often participate in meetings to understand model requirements, help optimize data storage for performance, and support the deployment of machine learning models into production environments. Effective collaboration involves continuous communication to troubleshoot data issues, implement data validation, and scale solutions as project needs evolve. This teamwork ensures that data-driven projects move efficiently from experimentation to deployment.

What is the difference between Data Engineer Ml vs Data Scientist?

AspectData Engineer MlData Scientist
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science certifications
Work EnvironmentBuilding data pipelines, managing databasesAnalyzing data, creating models
Employer & Industry UsageTech companies, finance, healthcareResearch institutions, tech firms, finance

Data Engineer Ml focuses on developing and maintaining data infrastructure and pipelines, while Data Scientists analyze data and build predictive models. Both roles often collaborate but serve different functions within data teams.

What are popular job titles related to Data Engineer Ml jobs in Iowa?

For Data Engineer Ml jobs in Iowa, the most frequently searched job titles are:

What cities in Iowa are hiring for Data Engineer Ml jobs?

Cities in Iowa with the most Data Engineer Ml job openings:

Infographic showing various Data Engineer Ml job openings in Iowa as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

AI Practitioner

West Des Moines, IA โ€ข On-site

$125 - $150/hr

Other

Posted 10 days ago


Job description

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.


Full Time Technical Office - Des Moines, IA West Des Moines, IA, US


POSITION PURPOSE

The AI Practitioner is an individual contributor responsible for driving the development, implementation, and optimization of AI-powered solutions across the enterprise. This role will play a key part in identifying opportunities to leverage Artificial Intelligence (AI) and Machine Learning (ML) to enhance operations, improve decision-making, and deliver innovation projects. The AI Practitioner will also support the โ€œcare and feedingโ€ of AI systems โ€” maintaining, improving, and monitoring AI tools, agents, and models to ensure ongoing value creation and ethical, responsible use of AI across the organization.


ACCOUNTABILITIES & PERFORMANCE EXPECTATIONS
AI Solution Development & Implementation
  • Design, develop, and deploy AI models, tools, and workflows to address identified business challenges and innovation opportunities.
  • Collaborate with business stakeholders to translate functional requirements into AI-driven solutions.
  • Evaluate and integrate third-party AI tools or APIs (e.g., large language models, predictive analytics, automation platforms).
  • Build and fine-tune AI models to support data analysis, customer insights, operational efficiency, and innovation initiatives.

AI Operations, Maintenance & Optimization
  • Oversee the lifecycle of deployed AI solutions, ensuring consistent performance, accuracy, and compliance.
  • Monitor AI agents, chatbots, and automation tools for output quality, model drift, and user adoption.
  • Conduct regular retraining, tuning, and improvement of AI models and workflows.
  • Implement governance and documentation standards for AI projects to ensure transparency and repeatability.

Cross-Functional Collaboration
  • Partner with data engineers, business analysts, and innovation leaders to identify use cases and prioritize AI opportunities.
  • Serve as an internal AI subject matter expert, advising teams on potential AI use and practical applications.
  • Communicate complex AI concepts to non-technical stakeholders in an accessible way.
  • Participate in project teams and proof-of-concept initiatives exploring new AI technologies or tools.
  • Stay current on emerging AI trends, technologies, and best practices.
  • Experiment with new AI models, frameworks, and methodologies to identify potential business applications.
  • Support internal knowledge-sharing initiatives and contribute to the development of an enterprise AI capability framework.

POSITION REQUIREMENTS
Education
  • Bachelorโ€™s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field (Masterโ€™s preferred but not required).

Experience
  • 2โ€“5 years of experience developing and implementing AI/ML solutions in an applied or enterprise environment.
  • Experience working with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and/or large language models (e.g., OpenAI, Anthropic, Azure OpenAI).
  • Familiarity with AI tools and APIs for automation, NLP, computer vision, or data processing.
  • Understanding of data management principles, prompt engineering, and AI model evaluation.

Skills
  • Strong programming skills (Python, SQL, R, or similar).
  • Ability to manage multiple AI projects with attention to accuracy, performance, and business alignment.
  • Strong problem-solving, analytical thinking, and communication skills.
  • Interest in human-AI collaboration, ethics, and responsible AI development.

Preferred Qualifications
  • Hands-on experience deploying AI models in production environments.
  • Prior experience supporting AI tools or agents used by business teams.
  • Exposure to innovation or digital transformation initiatives within an enterprise.

Key Attributes
  • Curious and continuously learning about emerging AI technologies.
  • Comfortable working in ambiguity and exploring new, unstructured problem areas.
  • Collaborative mindset with the ability to bridge technical and business perspectives.
  • Self-starter who thrives in fast-paced, evolving environments.

To perform this job successfully, an individual must be able to complete each essential duty satisfactorily. The requirements listed above are representative of the knowledge, skill and/or ability required.


ITA Group, Inc. is an Equal Opportunity Employer. In compliance with the Americans with Disabilities Act, the Company will consider reasonable accommodations for qualified individuals with disabilities and encourage prospective employees and incumbents to discuss potential accommodations with the Company.

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