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Ai Implementation Jobs in Madison, WI (NOW HIRING)

AgSource

Senior AI/ML Engineer

Watertown, WI · On-site +1

$99K - $136K/yr

Establish KPIs, track progress from the current to 100% adoption, implement interventions to ... Cloud AI infrastructure fluency, specifically Databricks and AWS. * Experiment design and ...

AgSource

Senior AI/ML Engineer

Watertown, WI · On-site

$99K - $136K/yr

Establish KPIs, track progress from the current to 100% adoption, implement interventions to ... Cloud AI infrastructure fluency, specifically Databricks and AWS. * Experiment design and ...

Urus Group LP

Senior AI/ML Engineer

Watertown, WI · On-site +1

$99K - $136K/yr

Establish KPIs, track progress from the current to 100% adoption, implement interventions to ... Cloud AI infrastructure fluency, specifically Databricks and AWS. * Experiment design and ...

Compeer Financial

AI Product Manager

Sun Prairie, WI · Hybrid

AI is rapidly changing what is possible in financial services and we're interested in more than ... implementation. * Turn learning into reusable practices, patterns and guidance that help other ...

Abbott

AI Platform Engineer

Madison, WI · On-site

Position Overview The AI Platform Engineer builds and operates the machine learning and generative ... Implement automated evaluation and promotion gates - performance benchmarks, regression checks, and ...

Abbott

AI Platform Engineer

Madison, WI · On-site

Position Overview The AI Platform Engineer builds and operates the machine learning and generative ... Implement automated evaluation and promotion gates - performance benchmarks, regression checks, and ...

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All JobsAi Implementation JobsAi Implementation Jobs in Madison, WI

Ai Implementation information

See Madison, WI salary details

$39.3K

$104.3K

$169.3K

How much do ai implementation jobs pay per year?

As of Sep 8, 2026, the average yearly pay for ai implementation in Madison, WI is $104,308.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,100.00 and $121,900.00 per year, depending on experience, location, and employer.

What is an AI implementation?

An AI Implementation job involves deploying artificial intelligence solutions within an organization to improve efficiency, automation, and decision-making. Professionals in this role work closely with data scientists, engineers, and business teams to integrate AI models into existing systems. They manage data pipelines, ensure model performance, and address challenges related to scalability and compliance. Strong technical skills, project management, and an understanding of business processes are essential for success in this role.

What are the key skills and qualifications needed to thrive in the AI implementation position?

To excel in AI Implementation, you need a robust understanding of machine learning concepts, data analysis, and software development, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, cloud platforms (AWS, Azure), and AI integration frameworks is commonly required, along with relevant certifications. Strong project management, problem-solving abilities, and excellent communication skills are crucial for coordinating with stakeholders and driving adoption. Mastering both technical and interpersonal skills ensures projects are delivered effectively and meet business objectives within diverse organizational settings.

What kinds of teams and departments does an AI implementation professional typically collaborate with?

AI Implementation professionals usually work cross-functionally, interacting with data scientists, software engineers, IT departments, and business stakeholders to ensure AI solutions address specific business needs. Regular collaboration with product managers and operations teams helps align technical efforts with strategic objectives and regulatory requirements. You may also work closely with end users to gather feedback, refine implementations, and ensure a smooth adoption process. This collaborative environment not only enhances the quality of AI deployments but also offers valuable exposure to different aspects of the organization, fostering professional growth.

How to become an AI implementation specialist?

To become an AI implementation specialist, individuals typically need a strong background in computer science, data science, or related fields, along with knowledge of machine learning, programming languages like Python, and AI frameworks such as TensorFlow or PyTorch. Gaining experience through internships, certifications, or projects involving AI deployment is also valuable. Continuous learning and staying updated on AI tools and industry trends are essential for success in this role.

How to get into AI implementation?

To pursue a career in AI implementation, develop strong skills in programming languages such as Python, understand machine learning frameworks like TensorFlow or PyTorch, and gain experience with data analysis and model deployment. Earning relevant certifications or degrees in computer science, data science, or AI can also enhance your qualifications.

What job categories do people searching Ai Implementation jobs in Madison, WI look for?

The top searched job categories for Ai Implementation jobs in Madison, WI are:

What cities near Madison, WI are hiring for Ai Implementation jobs?

Cities near Madison, WI with the most Ai Implementation job openings:

Ai Implementation jobs near you
Infographic showing various Ai Implementation job openings in Madison, WI as of August 2026, with employment types broken down into 75% Full Time, 21% Part Time, and 4% Contract. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution, with an average salary of $104,308 per year, or $50.1 per hour.

Senior AI/ML Engineer

AgSource

Watertown, WI • On-site, Remote

$99K - $136K/yr

Full-time

Posted 27 days ago

Key responsibilities

  • Lead the building of scalable real-time production-grade AI/ML applications that provide actionable intelligence on dairy farms.

  • Identify opportunities to apply AI for efficiency, growth, and customer value, and demonstrate how AI can address customer needs.

  • Establish AI governance frameworks, track AI adoption through KPIs, and communicate the impact of AI initiatives.

Job description


Turn decades of data into intelligence that helps feed the world.
VAS is the Operating System of the modern dairy with decades of longitudinal data for the most productive cows in the world. We hold a dominant US market position, and an expanding global reach.
We are seeking a Senior AI/ML Engineer to lead the building of scalable real-time production-grade applications that use AI/ML models to drive actionable intelligence on dairy farms. This is a strategic, hands-on position for an experienced technical leader who has a track record of shipping AI-enhanced customer applications and tooling used by engineering teams.
Our highly customizable on-farm systems give dairy owners unmatched flexibility in how they run their business. The right candidate sees that as a data challenge, where others will see it as an unsolvable mess.
RESPONSIBILITIES
AI Enablement
  • Understand customer challenges and how integrating AI capabilities can help lead to solutions that have AI as a differentiator.
  • Identify opportunities to apply AI for efficiency, growth, and customer value
  • Drive awareness of AI capabilities and demonstrate how it can address customer needs, improve efficiency, reduce costs, and drive growth
  • Drive transformation from AI-Ad Hoc to AI-Native engineering practices
  • Serve as an AI technical SME, conduct R&D to meet the needs of our AI strategy
  • Continuously assess emerging AI tools and make data-driven recommendations
  • Measure & Accelerate Adoption: Establish KPIs, track progress from the current to 100% adoption, implement interventions to accelerate uptake and communicate impact
  • Build Center of Excellence: Create forums for knowledge sharing, celebrate wins, and foster peer-to-peer learning
  • Cross-functional communication, explaining technical tradeoffs to product, dairy science, and engineering leadership in plain language.
  • Working with other enterprise stakeholders, establish AI governance frameworks and guardrails covering compliance, security, privacy, and ethical AI practices, and embed them into development workflows

Core AI Engineering Skills
  • Comfort across the full method spectrum, from classical statistics and operations research through machine learning to modern generative AI, choosing the simplest tool that solves the problem.
  • Data-wrangling skill with messy, distributed, legacy enterprise data sources, including inconsistent schemas and incomplete records.
  • Feature-engineering and data preprocessing for both structured farm data and unstructured sources.
  • Model selection and evaluation, knowing when linear regression, optimization, or a lookup table beats a neural network.
  • Production deployment experience, shipping models into real time applications rather than notebooks.
  • Cloud AI infrastructure fluency, specifically Databricks and AWS.
  • Experiment design and statistical rigor, being able to prove a model or method actually improves outcomes.
  • Translating ambiguous business or technical requirements into working systems.
  • Agentic and MCP experience

Evaluation, Testing & Observability
  • Build unit and behavioral tests for agents, tools, and workflows.
  • Develop tooling for trace analysis, agent state debugging, and hallucination tracking.
  • Compare and benchmark agent orchestration frameworks for trade-offs in speed, reliability, and usability.

Model Fine-Tuning & MLOps
  • Integrate, deploy, fine tune and monitor models in production using cloud providers.
  • Set up agent logging, observability dashboards, and recovery workflows.

Front-end & User Experience
  • Collaborate with front-end developers or build user-facing components using React, TypeScript.
  • Ensure seamless user and agent interaction via UI and API bridges.

EDUCATION & EXPERIENCE
Your background might include software engineering, data engineering, data science, machine learning engineering or AI engineering. What matters most is demonstrated technical depth and a track record of building and deploying AI/ML solutions in production.
  • Significant hands-on experience designing, building and deploying production AI/ML solutions.
  • Strong experience working with complex data, including distributed systems, inconsistent schemas and incomplete or legacy datasets.
  • Experience with feature engineering, model selection, experimentation and evaluation.
  • Strong understanding of descriptive, predictive, prescriptive and generative AI approaches.
  • Experience selecting and applying techniques across statistics, operations research, machine learning and deep learning.
  • Demonstrated experience taking models from experimentation through production deployment and monitoring.
  • Experience with deep learning frameworks and cloud-based AI services.
  • Experience with AWS and/or Databricks.
  • Experience or exposure to agentic architectures, MCP and AI orchestration frameworks.
  • Strong software engineering fundamentals and experience building scalable, production-quality systems.
  • Ability to translate ambiguous requirements into working solutions and clearly communicate technical decisions and tradeoffs.
  • Bachelor's degree in Software Engineering, Computer Science, Data Science, AI/ML or a related field preferred.

About Us
For the past 40 years we've woken up each day to support those that never stop feeding the world - and we have no plans to quit. We set the standard for farm management solutions and fix our eyes on raising the bar to meet the next generation of expectations.
Our software and information solutions help collect and connect a farm's data - from herd management to feed performance, tracking and more. These insights are a source of truth, empowering producers and their trusted advisors to make profit-driven and sustainable management decisions.
Whether near or far, large or small, VAS is at the heart of your dairy.
VAS has deep roots in the industry through its origin within the URUS family of companies. As a holding company with cooperative and private ownership, URUS is a family of businesses at the heart of the dairy and beef industry - Alta Genetics, GENEX, Genetics Australia, Leachman Cattle, Jetstream, PEAK, SCCL, Trans Ova Genetics and VAS. Each organization has its unique identity, products, and services. These companies work globally to provide cutting-edge dairy and beef genetics, customized reproductive services to maximize conceptions, dairy management information to take producers to the frontline of progressive dairy farming, and an array of products and services to help bovines reach their full genetic potential. URUS has 9 brands in 17 retail countries and employs nearly 2,800 people globally.

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