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Machine Learning Developer Intern Jobs in Mazomanie, WI

Senior AI Engineer

Madison, WI · On-site

$105K - $144K/yr

This position blends applied machine learning, software engineering, cloud architecture, and end-to-end solution delivery. Success in this role requires a strong understanding that production AI ...

... AI, machine learning, and large-scale data analysis. Deployment Pipelines and Continuous Integration (CI/CD) Build and manage secure, automated CI/CD pipelines for data engineering workflows ...

Are you interested in applying machine learning or data mining on problems that truly improve ... Programming capabilities including C++, Java, Python is a plus but not necessary. Additional ...

Python Tutor

Madison, WI · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

Currently pursuing a Bachelor of Science degree in engineering. Minimum 2.8 GPA Experience ... We cultivate a learning environment, dedicating tools and resources to ensure we remain at the ...

Data Science Tutor

Madison, WI · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Our team of data scientists, machine learning engineers, revenue cycle professionals, and certified application specialists would love for you to join us. Payroll Manager at Cardamom Hybrid in ...

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Showing results 1-20

Machine Learning Developer Intern information

See Mazomanie, WI salary details

$25.3K

$42.2K

$87.2K

How much do machine learning developer intern jobs pay per year?

As of Jul 13, 2026, the average yearly pay for machine learning developer intern in Mazomanie, WI is $42,188.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

How do Machine Learning Developer Interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What does a Machine Learning Developer Intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

What are the key skills and qualifications needed to thrive as a Machine Learning Developer Intern, and why are they important?

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

Senior AI Engineer

Senior AI Engineer

Cliftonlarsonallen

Madison, WI • On-site

$105K - $144K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 22 days ago


CliftonLarsonAllen rating

7.4

Company rating: 7.4 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

15th of 17 rated bookkeepers and accountants


Job description

CLA is a top 10 national professional services firm where our purpose is to create opportunities every day, for our clients, our people, and our communities through industry-focused wealth advisory, digital, audit, tax, consulting, and outsourcing services. Even with more than 8,500 people, 130 U.S. locations, and a global reach, we promise to know you and help you.

CLA is dedicated to building a culture that invites different beliefs and perspectives to the table, so we can truly know and help our clients, communities, and each other.

CLA is currently seeking a Senior AI Engineer to join our growing CLA Digital - Data and Automation Team. The Senior AI Engineer will lead the design and implementation of production-grade AI solutions across machine learning, optimization, and generative AI. This role is ideal for someone who can translate business problems into scalable, reliable technical solutions that perform in real-world environments.

You will work closely with AI leadership while providing day-to-day technical guidance to junior team members. This position blends applied machine learning, software engineering, cloud architecture, and end-to-end solution delivery. Success in this role requires a strong understanding that production AI involves far more than model development-it includes evaluation, observability, integration, governance, and operational excellence.

About the role:

AI Solution Development & Architecture

  • Lead the implementation of production-ready AI systems across predictive modeling, optimization, and LLM-powered applications
  • Design end-to-end architectures including data pipelines, APIs, model services, orchestration layers, and monitoring systems
  • Build and deploy AI workflows within Azure and Databricks environments
  • Develop robust evaluation frameworks for both ML models and LLM-based systems
  • Design and implement AI applications with strong grounding, safety, evaluation, and cost controls
  • Build AI workflows including tool integration, memory systems, and orchestration logic
  • Implement model routing, fallback strategies, and guardrails
  • Develop context and memory systems (retrieval, summarization, session continuity)
Evaluation, Safety & Reliability
  • Establish robust evaluation frameworks for ML and LLM systems
  • Define and monitor:
    • Task success metrics and regression testing
    • Hallucination and grounding performance
    • Safety risks (prompt injection, data leakage)
  • Implement observability practices including logging, tracing, and monitoring
  • Ensure system reliability through testing, deployment standards, and incident readiness
Technical Leadership
  • Translate ambiguous business needs into clear technical designs and delivery plans
  • Provide mentorship and technical oversight to junior engineers
  • Lead architecture reviews, code reviews, and technical design discussions
  • Establish engineering standards across testing, CI/CD, deployment, and monitoring
Cross-Functional Collaboration
  • Partner with product, engineering, security, and business stakeholders
  • Support solution design, feasibility assessments, and delivery planning
  • Contribute to proposals, technical narratives, and client-facing engagements
Core Responsibilities
  • Own major technical workstreams for AI delivery from design through deployment
  • Build scalable data and model pipelines for batch and real-time use cases
  • Lead development of LLM-based applications with strong grounding, evaluation, safety, and cost controls
  • Implement classical AI and advanced analytics approaches including forecasting, anomaly detection, optimization, recommendation, and decision support
  • Define and implement MLOps and LLMOps standards including versioning, deployment, monitoring, and rollback strategies
  • Design secure and supportable integrations across enterprise systems, APIs, and data platforms
  • Evaluate tradeoffs across tools, frameworks, and architecture choices in Azure and Databricks
  • Troubleshoot complex issues in production environments across data, infrastructure, and application layers
  • Drive technical quality and ensure solutions are maintainable, scalable, and aligned to client needs
  • Support business development by contributing to solution framing, estimates, and technical narratives

What you will need:

  • 2 years of relevant experience required
  • 5-7 years of experience in AI engineering, machine learning, or software engineering preferred
  • Strong proficiency in Python and production-grade development practices preferred
  • Proven experience deploying ML/AI systems into production environments preferred
  • Experience designing APIs, pipelines, and service-oriented architectures preferred
  • Strong understanding of model evaluation, experimentation, and performance tradeoffs preferred
  • Ability to work independently and mentor junior team members
  • Strong communication skills across technical and non-technical audiences

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Wellness at CLA

To support our CLA family members, we focus on their physical, financial, social, and emotional well-being and offer comprehensive benefit options that include health, dental, vision, 401k and much more.


To view a complete list of benefits, click here.



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About CliftonLarsonAllen

Sourced by ZipRecruiter

CliftonLarsonAllen (CLA) is a leading professional services company based in Minneapolis, MN, US. CLA operates in the accounting industry and offers a broad range of products and services such as wealth advisory, outsourcing, audit, tax, and consulting services. The company was founded in 1953 with a merger between two firms, Clifton Gunderson and LarsonAllen, in 2012. Working in accordance with their mission to create opportunities for clients, people, and communities, they have established a presence across the US, serving privately held businesses, non-profits, and governmental entities. Recognized for their contributions, CLA has received accolades such as the Innovative Firm of the Year award.

Industry

Accounting services

Company size

5,001 - 10,000 Employees

Headquarters location

Minneapolis, MN, US

Year founded

2012