ZipRecruiter

Log In

1

Internship Machine Learning Engineer Jobs in Mazomanie, WI

Bespoke Labs

Machine Learning Engineer

Madison, WI · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Paradigm

Senior ML Ops Engineer

Middleton, WI · On-site

$123K - $170K/yr

... end-to-end machine learning lifecycle, including model training, deployment, monitoring, and ... Engineers, and Infrastructure teams to operationalize ML solutions and improve deployment ...

Insperity

Artificial Intelligence Engineer III

Madison, WI · On-site

$58 - $77.75/hr

This role applies advanced software, data science, machine learning, and LLM engineering expertise to build AI powered applications, model driven solutions, and intelligently automated workflows. The ...

Insperity

Artificial Intelligence Engineer III

Madison, WI

$58 - $77.75/hr

This role applies advanced software, data science, machine learning, and LLM engineering expertise to build AI powered applications, model driven solutions, and intelligently automated workflows. The ...

Insperity

Artificial Intelligence Engineer III

Madison, WI · On-site

$58 - $77.75/hr

This role applies advanced software, data science, machine learning, and LLM engineering expertise to build AI powered applications, model driven solutions, and intelligently automated workflows. The ...

Insperity

Artificial Intelligence Engineer III

Madison, WI

$58 - $77.75/hr

This role applies advanced software, data science, machine learning, and LLM engineering expertise to build AI powered applications, model driven solutions, and intelligently automated workflows. The ...

Springs Window Fashions

AI Engineer II

Middleton, WI

$100K - $137K/yr

Write, test, and ship real AI and machine learning code that makes it into production, with support from senior engineers. * Build features for generative AI applications--LLMs, RAG, copilots, and ...

New

Springs Window Fashions

AI Engineer II

Middleton, WI

$100K - $137K/yr

Write, test, and ship real AI and machine learning code that makes it into production, with support from senior engineers. * Build features for generative AI applications-LLMs, RAG, copilots, and ...

Springs Window Fashions

AI Engineer II

Middleton, WI · On-site

$100K - $137K/yr

Write, test, and ship real AI and machine learning code that makes it into production, with support from senior engineers. * Build features for generative AI applications-LLMs, RAG, copilots, and ...

New

Paradigm

Senior Applied ML Engineer

Middleton, WI · Remote

$125K - $183K/yr

We are looking for a Senior Applied ML Engineer to design, implement, and scale machine learning systems that power next-generation construction and digital twin solutions. You will apply advanced ML ...

Springs Window Fashions

Senior AI Engineer

Middleton, WI

$107K - $147K/yr

The Sr AI Engineer is a hands-on technical leader who ships enterprise-scale AI into production and ... Design, build, ship, and own enterprise AI and machine learning solutions in production. * Build ...

next page

Showing results 1-20

All JobsMachine Learning Engineer JobsInternship Machine Learning Engineer JobsInternship Machine Learning Engineer Jobs in Mazomanie, WI

Internship Machine Learning Engineer information

See Mazomanie, WI salary details

$25.3K

$42.2K

$87.2K

How much do internship machine learning engineer jobs pay per year?

As of Aug 1, 2026, the average yearly pay for internship machine learning engineer 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.

What does an Internship Machine Learning Engineer do?

An Internship Machine Learning Engineer works alongside experienced engineers to help develop, test, and deploy machine learning models. Their responsibilities may include cleaning and preparing data, writing code for model training, evaluating model performance, and contributing to research tasks. Interns often learn to use popular frameworks such as TensorFlow or PyTorch and gain hands-on experience with real-world datasets. This role is designed to help students or recent graduates apply their academic knowledge to practical problems while developing industry-relevant skills.

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

AspectInternship Machine Learning EngineerData Scientist Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, data analysis, programming
Work EnvironmentDeveloping ML models, coding, testingData analysis, visualization, reporting
Employer & Industry UsageTech companies, startups, AI firmsTech, finance, healthcare, consulting

Internship Machine Learning Engineers focus on developing and testing machine learning models, often requiring programming and basic ML knowledge. Data Scientist Interns analyze data, create visualizations, and generate insights. Both roles are common in tech and data-driven industries, but ML Engineer internships emphasize model deployment, while Data Science internships focus on data analysis and reporting.

What types of projects and responsibilities can I expect as an Internship Machine Learning Engineer?

As an Internship Machine Learning Engineer, you will typically support the development, testing, and deployment of machine learning models under the guidance of senior engineers. Your responsibilities may include data preprocessing, exploratory data analysis, implementing algorithms, and evaluating model performance. You'll often collaborate closely with data scientists, software engineers, and product managers, gaining exposure to real-world workflows and tools. This hands-on experience is invaluable for building technical skills and understanding how machine learning solutions are integrated into larger products.

What are the key skills and qualifications needed to thrive as an Internship Machine Learning Engineer, and why are they important?

To excel as an Internship Machine Learning Engineer, you typically need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, often supported by coursework or relevant project experience. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is common, along with proficiency in data processing libraries. Curiosity, strong problem-solving abilities, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can contribute meaningfully to projects, adapt to new challenges, and collaborate productively in a rapidly evolving technical environment.
Internship Machine Learning Engineer jobs near you

Machine Learning Engineer

Bespoke Labs

Madison, WI • On-site

Full-time

Re-posted 14 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

Apply