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Ai Computer Science Jobs in Madison, WI (NOW HIRING)

Senior AI Integration Analyst

Madison, WI ยท On-site

$91K - $155K/yr

Bachelor's degree in engineering, physics, computer science, math, information systems, statistics, or related field or Associates degree and 2+ years of related experience or High School/GED and 4+ ...

Java Tutor

Madison, WI ยท Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Familiar with Java curricula including AP Computer Science A and college-level courses, and common ...

Discrete Math Tutor

Madison, WI ยท Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... students for computer science theory, cryptography, and advanced mathematics coursework.

Artificial Intelligence Engineer III

Madison, WI ยท On-site

$58 - $77.75/hr

Contributes to the establishment and evolution of AI engineering standards, patterns, and best practices. Qualifications: * Bachelor's degree in Computer Science, Software Engineering, Data Science ...

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Ai Computer Science information

See Madison, WI salary details

$50.9K

$112.2K

$138.6K

How much do ai computer science jobs pay per year?

As of Jul 14, 2026, the average yearly pay for ai computer science in Madison, WI is $112,209.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,200.00 and $138,100.00 per year, depending on experience, location, and employer.

What is the difference between Ai Computer Science vs Data Scientist?

AspectAi Computer ScienceData Scientist
Required CredentialsBachelor's or higher in CS, AI, or related fields; certifications in AI/MLBachelor's or higher in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentResearch labs, tech companies, AI startupsBusiness environments, analytics teams, tech firms
Industry UsageDeveloping AI algorithms, machine learning models, AI systemsAnalyzing data, building predictive models, data visualization

Ai Computer Science focuses on developing AI algorithms and systems, often requiring advanced technical skills in machine learning and programming. Data Scientists analyze data to extract insights, build models, and support decision-making. While both roles involve machine learning, Ai Computer Science is more research and development-oriented, whereas Data Scientists focus on applying data analysis techniques to solve business problems.

What are the typical challenges faced when working on AI projects within a computer science team?

One common challenge in AI computer science roles is managing the balance between research and practical implementation. Teams often face difficulties with limited or imperfect datasets, ensuring models generalize well beyond training data, and integrating AI solutions into existing systems. Collaboration with data engineers, domain experts, and product managers is crucial to ensure the developed AI solutions align with business objectives and user needs. Additionally, staying updated with rapidly evolving AI technologies and addressing ethical considerations are ongoing parts of the role.

What is AI in computer science?

AI, or Artificial Intelligence, in computer science refers to the simulation of human intelligence by machines, especially computer systems. It involves creating algorithms and software that allow computers to perform tasks that typically require human intelligence, such as learning, reasoning, problem-solving, perception, and language understanding. AI encompasses various subfields, including machine learning, natural language processing, robotics, and computer vision. The goal of AI is to build systems that can function autonomously and improve over time through experience.

What are the key skills and qualifications needed to thrive as an AI Computer Scientist, and why are they important?

To thrive as an AI Computer Scientist, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree or higher qualifications. Proficiency in programming languages such as Python, experience with AI frameworks like TensorFlow or PyTorch, and familiarity with data analysis tools are essential. Critical thinking, creativity, and strong collaboration skills help drive innovation and effective problem-solving in cross-functional teams. These competencies are vital for developing advanced AI solutions and ensuring their successful real-world application.
What are the most commonly searched types of Ai Computer Science jobs in Madison, WI? The most popular types of Ai Computer Science jobs in Madison, WI are:
What are popular job titles related to Ai Computer Science jobs in Madison, WI? For Ai Computer Science jobs in Madison, WI, the most frequently searched job titles are:
What job categories do people searching Ai Computer Science jobs in Madison, WI look for? The top searched job categories for Ai Computer Science jobs in Madison, WI are:
Infographic showing various Ai Computer Science job openings in Madison, WI as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $112,209 per year, or $53.9 per hour.

Technical Architect - Data, Analytics & AI

Munich Re

Madison, WI โ€ข Hybrid

$64.25 - $82.50/hr

Other

Medical, Life, Retirement, PTO

Re-posted 7 days ago


Job description

Location: Princeton, New Jersey Hybrid 40-50% onsiteย 

Role Overview

We are seeking aย Technical Architect (TA) with deep expertise in Data, Analytics, and Artificial Intelligence (AI) to join the IT Enterprise Architecture organization. This role is accountable for proactively leading data, analytics, and AIdriven technology transformation initiatives and enabling measurable business outcomes across the enterprise.

The Technical Architect will play a critical role inย transforming local, legacy, datadriven processes, and systems into centralized, scalable, and groupwide platforms, while ensuring alignment with enterprise architecture standards and business strategy.

Technical Architects provide technical leadership acrossย analysis, design, facilitation, and execution, supporting the evolution of enterprise Data, Analytics, and AI capabilities and the associated application portfolios and technology stacks. The role owns the creation of key architectural deliverables such as targetstate architectures, transformation roadmaps, standards, and guidelines to enable successful project delivery and longterm strategic outcomes.

This position is based in the USA and ensures that Data, Analytics, and AI architecture vision, principles, and standards are consistently executed through a common enterprise framework, with a strong emphasis on cloudbased data platforms, AI enablement, and data governance.

The ideal candidate will help advance organizational directives around simplification, modernization, and innovation by providing architectural leadership in enterprise data platforms, integration components, and AIenabled data strategies.

Key Responsibilities

  • Assist in the development of a multiyear Data, Analytics, and AI roadmap, aligned with the Munich Re Target Architecture and Roadmap Development Process, in collaboration with Data & Analytics Enterprise Architects.
  • Drive standardization of Data, Analytics, and AI technology standards, principles, and guidelines across multiple business entities.
  • Define and maintain technical standards for enterprise data management, analytics platforms, and AI enablement capabilities.
  • Design and guide datacentric and AIenabled initiatives, supporting the transition from traditional data architectures to nextgeneration cloud, analytics, and AI platforms.
  • Act as an evangelist and ambassador for enterprise architecture standards including Data Governance. Data Intake and Ingestion. Data Modeling, Data Integration, Analytics and AI lifecycle management
  • Collaborate closely with Business Solutions teams, Technology Architects, and Enterprise Data Architects across initiatives and implementations.
  • Identify technologyrelated business pain points by mapping business capabilities to current platforms, leveraging EA practices and participating in innovation activities, including AI adoption.
  • Enable IT development and infrastructure teams to make informed technology decisions through frameworks, reference architectures, standards, and reusable patterns.
  • Identify technical risks, architectural gaps, and vulnerabilities that could impact project delivery or lead to postrelease defects.
  • Reduce cost and complexity through standardization, reuse, and rationalization of data, analytics, and AI platforms.
  • Partner with EA and TA peers (enterprise, solution, and business architects) to derive the futurestate technology architecture, aligned to business strategy and external trends.
  • Define migration and transformation plans to close gaps between current and target states, in alignment with Business Solutions and Business Technology Architects.
  • Support governance, assurance, and compliance activities to ensure alignment with enterprise architecture standards and policies.
  • Assess and articulate the organizational, skills, process, and financial impact of changes to the application portfolio, data platforms, and AI stack.
  • Define and govern enterprise AI architecture standards, including model lifecycle management, MLOps, and AI platform integration.
  • Ensure responsible and compliant AI adoption, aligned with AI governance, model risk management, data privacy, and security controls.
  • Guide the integration of AI/ML capabilities into analytics platforms, including predictive, prescriptive, and generative AI use cases.
  • 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, versioning, and retraining in cloud environments.
  • Evaluate emerging AI technologies, tools, and platforms and provide strategic recommendations for enterprise adoption.

ย 

Your Profile

  • 4+ years of experience in Enterprise Architecture or Technical Architecture.
  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, Mathematics, or Business (or equivalent).
  • Strong experience with cloud platforms and services, including:
    • Azure (e.g.; Azure AI Studio, Azure Data Services and tools)
    • AWSย  (e.g.; Amazon Bedrock, Sagemaker, Data Services and tools)
    • Databricks
  • Handson experience with enterprise data concepts, including:
    • Data Intake and Ingestion
    • Data Warehousing
    • Data Lakes / Lakehouse architectures
    • ETL / ELT
    • Interactive and operational reporting
    • Statistical and regulatory reporting
    • Master Data Management (MDM)
    • Data Governance, Quality, Security, Audit, Balance & Control
  • Solid understanding of enterprise architecture practices, including:
    • Architectural patterns
    • Roadmaps
    • Architecture Review Boards
    • Solution Design Boards
  • Experience defining data management and AI roadmaps, cloudbased services, and reusable architectural patterns.
  • Experience integrating operational data with enterprise data lakes.
  • Strong understanding of data integration challenges and solution patterns.
  • Experience with statistical and data science languages such as Python and R (strong asset).
  • Exposure to AI/ML concepts, including model development, deployment, monitoring, and MLOps (required).
  • Familiarity with Generative AI concepts, AI platforms, and enterprise adoption considerations (strong asset).
  • Strong business acumen with deep understanding of:
    • Financial systems
    • Corporate and backoffice systems
    • Enterprise data management, analytics, and AI technology landscape
  • Strong problemsolving skills, unquestioned integrity, and high collaboration capability.
  • Passion for innovation, continuous improvement, modernization, and change management.
  • Excellent written and verbal communication skills, with the ability to communicate effectively at all levels.
  • High sense of ownership, accountability, and pride in delivered outcomes.

At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on providing our customers the most innovative products and services.

We are an equal opportunity employer. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

The Company is open to considering candidates in Princeton, NJ. The salary range posted below applies to the Company's Princeton location.

The base salary range anticipated for this position isย $141,800 - $207,900ย plus opportunity for company bonus based upon a percentage of eligible pay.ย  In addition, the company makes available a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, 401k match, retirement savings plan, paid holidays and paid time off (PTO).ย 

The salary estimate displayed represents the typical salary range for candidates hired in this position in Princeton. Factors that may be used to determine your actual salary include your specific skills, how many years of experience you have and comparison to other employees already in this role. Most candidates will start in the bottom half of the range.ย