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Patterned Learning Ai Jobs in Chicago, IL (NOW HIRING)

Abbott

IT Director, Data & AI Architecture

Waukegan, IL · On-site

Establish design patterns supporting structured, semi-structured, streaming, and unstructured data ... Architect AI-ready data ecosystems supporting machine learning, generative AI, predictive analytics ...

ZS

AI Engineering Specialist

Evanston, IL · On-site

$155K - $167K/yr

Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ... patterns like RAG, Agentic workflows, PEFT (e.g. LORA, QLORA, etc.) • Responsible for the ...

CNA

System Architect Director - AI Innovation

Chicago, IL · On-site

$250K/yr

Applied AI / GenAI depth including LLM solution patterns, prompt engineering, model selection ... Master's degree in Artificial Intelligence, Machine Learning, Data Science, Software Engineering ...

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How much do patterned learning ai jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for patterned learning ai in Chicago, IL is $41.92, according to ZipRecruiter salary data. Most workers in this role earn between $30.48 and $54.47 per hour, depending on experience, location, and employer.

What are some typical challenges faced by patterned learning AI professionals in implementing AI-driven solutions within organizations?

Patterned Learning AI professionals often encounter challenges such as integrating AI models with existing legacy systems, ensuring high-quality and representative training data, and aligning AI solutions with specific business objectives. Collaboration across multidisciplinary teams—including data scientists, software engineers, and business stakeholders—is essential for successful deployment. Additionally, professionals must stay updated on evolving AI technologies and best practices to maintain model accuracy and address ethical considerations.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (especially Python), and a degree in computer science or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, as well as familiarity with cloud computing platforms and data management tools, is essential. Excellent problem-solving skills, creativity, and clear communication are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies are vital for developing reliable AI systems that solve real-world problems and drive innovation.

What is the difference between Patterned Learning Ai vs Data Scientist?

AspectPatterned Learning AiData Scientist
Required CredentialsTypically requires machine learning, AI, or computer science degrees; certifications in AI toolsRequires degrees in statistics, computer science, or related fields; often certifications in data analysis
Work EnvironmentTech companies, AI startups, research labs focusing on AI developmentBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed by AI-focused organizations developing intelligent systemsEmployed across industries for data analysis, predictive modeling, and decision support

Patterned Learning Ai primarily focuses on developing AI models and algorithms, often requiring specialized technical skills. Data Scientists analyze data to extract insights and inform business decisions. While both roles involve data and machine learning, Patterned Learning Ai is more centered on creating AI systems, whereas Data Scientists interpret data for strategic purposes.

What is patterned learning AI?

Patterned Learning AI refers to artificial intelligence systems designed to recognize, learn from, and replicate patterns in data. These systems use algorithms to identify trends, correlations, and structures within large datasets, enabling them to make predictions or automate decision-making processes. Patterned Learning AI is commonly used in fields like image recognition, natural language processing, and predictive analytics. Its applications help businesses and researchers uncover hidden insights, streamline operations, and improve accuracy in various tasks.
What are popular job titles related to Patterned Learning Ai jobs in Chicago, IL? For Patterned Learning Ai jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Patterned Learning Ai jobs in Chicago, IL look for? The top searched job categories for Patterned Learning Ai jobs in Chicago, IL are:
Patterned Learning Ai jobs near you
Infographic showing various Patterned Learning Ai job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $87,200 per year, or $41.9 per hour.

Director, AI Engineering & Delivery

Vizient

Chicago, IL

Full-time

Re-posted 23 days ago

Job description

When you're the best, we're the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.

Summary

In this role, you will lead the execution, operationalization, scaling, and continuous improvement of enterprise AI engineering and delivery initiatives across Vizient. You will implement scalable AI engineering practices, AI delivery operating models, AIOps and LLMOps capabilities, and cross-functional engineering standards that enable the organization to rapidly and responsibly deliver AI-powered business outcomes, operational efficiencies, and scalable enterprise value. You will partner closely with business, technology, governance, automation, architecture, and quality engineering teams to build production-grade AI applications, agentic workflows, reusable platform capabilities, and operational processes that support Vizient's enterprise AI transformation strategy.

Responsibilities

Lead the execution and delivery of enterprise AI engineering initiatives, including AI-powered applications, LLM-enabled workflows, agentic orchestration solutions, AI-enabled automation capabilities, and platform integrations

Drive day-to-day engineering delivery activities across AI teams, including sprint execution, backlog management, delivery tracking, issue resolution, dependency management, and operational execution

Implement and operationalize enterprise AI engineering practices, including AI software development lifecycle (SDLC) processes, deployment standards, runtime observability, release management, and engineering quality practices

Provide technical oversight across solution design, development, validation, deployment, monitoring, optimization, and production support activities

Support AIOps and LLMOps operational practices, including runtime monitoring, drift detection, observability, incident management, prompt lifecycle management, evaluation execution, operational telemetry, and production reliability

Develop reusable AI engineering patterns, implementation playbooks, shared services, templates, internal libraries, and engineering accelerators to improve delivery consistency, scalability, and operational efficiency

Drive adoption of enterprise engineering standards, scalable delivery practices, and shared implementation patterns across AI delivery teams

Partner with AI Governance, Quality Engineering, Automation, Architecture, and AI Delivery Lifecycle teams to operationalize governance requirements, validation processes, responsible AI controls, runtime safeguards, and secure delivery practices

Coordinate AI delivery activities across teams, including operational planning, resource management, contractor and vendor alignment, knowledge transfer, and delivery continuity

Partner with cross-functional stakeholders to support technical feasibility assessments, delivery readiness activities, implementation planning, and engineering sustainability efforts

Support vendor evaluations, platform implementation initiatives, build-versus-buy assessments, and engineering modernization efforts

Lead, mentor, and develop engineering managers, architects, engineers, and contractor teams while fostering a high-performing, collaborative, and continuously learning culture

Communicate delivery progress, operational risks, technical updates, engineering tradeoffs, and implementation recommendations to technical and business leaders

Research and evaluate emerging AI engineering, automation, observability, orchestration, and platform technologies to support innovation and continuous improvement

Qualifications

Relevant degree preferred

7 or more years of experience in software engineering, AI application engineering, engineering delivery, platform engineering, or enterprise technology functions required

3 or more years of experience leading engineering teams, delivery organizations, or large-scale technology initiatives required

Experience leading distributed teams, contractor/vendor coordination, and large-scale engineering delivery initiatives within complex and evolving operational environments required

Hands-on experience designing, delivering, and operationalizing production AI solutions leveraging large language models (LLMs), APIs, agentic workflows, orchestration frameworks, and modern AI engineering patterns required

Experience implementing and scaling engineering operating models, AI delivery frameworks, agile delivery ecosystems, or enterprise engineering practices required

Strong analytical, problem-solving, communication, presentation, stakeholder management, and cross-functional collaboration skills required

Ability to manage multiple priorities in fast-paced, evolving, and deadline-driven environments required

Experience with cloud platforms, APIs, data integration, DevOps practices, automation frameworks, and modern software engineering tools preferred

Experience operating in healthcare or other regulated environments preferred

Strong understanding of responsible AI concepts, including governance, human oversight, model monitoring, operational risk management, AI security considerations, and secure operationalization of AI solutions within enterprise environments preferred

Healthcare industry experience, including familiarity with HIPAA, SOC 2, or other regulated data environments preferred

Experience with AI-enabled automation, intelligent orchestration, evaluation pipelines, operational AI delivery practices, and agentic frameworks preferred

Demonstrated ability to balance execution excellence, operational scalability, governance, and engineering delivery effectiveness preferred

You must be authorized to work in the United States without sponsorship.

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Estimated Hiring Range:

At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $117,600.00 to $206,000.00.

This position is also incentive eligible.

Vizient has a comprehensive benefits plan! Please view our benefits here:

http://www.vizientinc.com/about-us/careers

Equal Opportunity Employer: Females/Minorities/Veterans/Individuals with Disabilities

The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.

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