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Nvidia Machine Learning Internship Jobs in Chicago, IL

Prior internship, research, or applied ML project experience with measurable outcomes What You'll Gain * Ownership of real machine learning experiments with direct business visibility * Experience ...

Sr. Machine Learning Engineer

Schaumburg, IL · On-site

$103K - $141.40K/yr

I wont accept opts with internships Actalent/Peyton Hello Muni, We received a new role from Toyota. Max rate is 95/hr. Toyota Connected's Mobility team is looking for a Sr. Machine Learning Engineer ...

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$107.60K - $147.80K/yr

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... At least 4 years of experience programming with Python, Scala, or Java (Internship experience does ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... NVIDIA DGX Spark. Understanding of FDA regulatory requirements for AI/ML in medical devices ...

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Nvidia Machine Learning Internship information

See Chicago, IL salary details

$26.3K

$43.9K

$90.7K

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

As of May 28, 2026, the average yearly pay for nvidia machine learning internship in Chicago, IL is $43,867.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,500.00 and $47,400.00 per year, depending on experience, location, and employer.

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

To excel as an Nvidia Machine Learning Intern, you need a solid foundation in computer science, mathematics, and machine learning concepts, typically supported by progress toward a relevant degree. Familiarity with programming languages like Python, deep learning frameworks such as TensorFlow or PyTorch, and GPU computing tools (e.g., CUDA) is essential. Strong analytical thinking, problem-solving skills, and effective teamwork set standout interns apart. These competencies enable you to contribute meaningfully to advanced AI projects and collaborate efficiently within Nvidia's innovative environment.

What types of projects do interns typically work on during the Nvidia Machine Learning Internship?

During the Nvidia Machine Learning Internship, interns often work on real-world projects involving deep learning, computer vision, or natural language processing. These projects may include developing new models, optimizing existing algorithms, or contributing to open-source frameworks. Interns typically collaborate with experienced engineers and researchers, gaining hands-on experience while having access to state-of-the-art GPU hardware. The work environment encourages innovation and learning, and interns are often given opportunities to present their results to senior team members.

What is an Nvidia Machine Learning Internship?

An Nvidia Machine Learning Internship is a temporary, hands-on program for students or recent graduates to work with Nvidia’s teams on projects related to machine learning and artificial intelligence. Interns typically assist with research, data analysis, model development, and software engineering tasks using Nvidia’s cutting-edge GPU technologies. The internship provides valuable real-world experience, mentorship from industry experts, and the opportunity to contribute to innovative AI solutions. It’s a great way to build skills, expand your professional network, and potentially secure a full-time role at Nvidia in the future.

What is the difference between Nvidia Machine Learning Internship vs Data Science Internship?

AspectNvidia Machine Learning InternshipData Science Internship
Required CredentialsRelevant coursework, programming skills, possibly some machine learning certificationsStatistics, programming, data analysis skills, often a related degree
Work EnvironmentResearch labs, tech company offices, collaborative teams focused on AI/ML projectsBusiness environments, data analysis teams, cross-functional collaboration
Employer & Industry UsageTech companies, AI/ML research labs, hardware/software firms like NvidiaVarious industries including tech, finance, healthcare, and consulting

While both internships involve working with data and programming, Nvidia Machine Learning Internships focus specifically on developing and optimizing machine learning models in a hardware and AI context, whereas Data Science Internships emphasize analyzing data to derive insights across diverse industries.

What are the most commonly searched types of Nvidia Machine Learning jobs in Chicago, IL? The most popular types of Nvidia Machine Learning jobs in Chicago, IL are:
What are popular job titles related to Nvidia Machine Learning Internship jobs in Chicago, IL? For Nvidia Machine Learning Internship jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Nvidia Machine Learning Internship jobs in Chicago, IL look for? The top searched job categories for Nvidia Machine Learning Internship jobs in Chicago, IL are:
Machine Learning Co-Op

Machine Learning Co-Op

Kop-Coat, Inc.

Vernon Hills, IL • On-site

$28 - $30/hr

Full-time

Posted 7 days ago


Job description

CoOp Student - Machine Learning & Applied AI

Location: Hybrid - Minimum 3 days per week onsite (Vernon Hills, IL)
Duration: CoOp Term (6-8 months)
Department: Automation & Emerging Technology
Reports To: Emerging Technologies Leader
Candidate Level: Bachelor's, Master's, or PhDtrack students


Position Overview

We are seeking a highly motivated Machine Learning & Applied AI CoOp Student to join our Automation & Emerging Technology team. This role is ideal for students who want handson ownership of realworld machine learning experiments in a fastmoving, startuplike environment within a large enterprise.

The coop will focus on applied machine learning, datadriven experimentation, and model evaluation, with opportunities to explore Generative AI and large language models where they meaningfully support MLdriven use cases. Rather than production maintenance or traditional automation work, this role emphasizes problem framing, experimentation, and measurable impact.

This position follows a hybrid work model, with a minimum of three (3) days per week onsite at our Vernon Hills, IL office.


Key Responsibilities

  • Lead machine learning experiments endtoend, including:
    • Problem definition and hypothesis development
    • Data exploration and feature engineering
    • Model prototyping, training, and evaluation
    • Iteration based on quantitative results
  • Develop and evaluate ML models using enterprise datasets for use cases such as:
    • Prediction and classification
    • Pattern detection and insight generation
    • Decision support and optimization
  • Apply sound experimental design and evaluation techniques, including:
    • Train/validation/test strategies
    • Baseline comparisons
    • Error analysis and model diagnostics
  • Use Databricks for data analysis, experimentation, and scalable ML workflows
  • Define and track success metrics, such as:
    • Model accuracy, precision/recall, and robustness
    • Latency, scalability, and cost considerations
    • Business relevance and usability
  • Explore applied AI techniques, including Generative AI and LLMs, where appropriate (e.g., summarization, knowledge retrieval, or hybrid ML + LLM solutions)
  • Document experiments, assumptions, results, and technical tradeoffs; present findings and demos to technical and business stakeholders
  • Apply Responsible AI and data governance practices, including data privacy, security, and bias awareness

Required Qualifications

  • Currently enrolled in a Bachelor's, Master's, or PhDtrack program in Computer Science, Data Science, Machine Learning, Statistics, or a related field
  • Ability to work onsite in Vernon Hills, IL at least three days per week
  • Strong proficiency in Python
  • Solid understanding of core machine learning concepts, such as:
    • Supervised and unsupervised learning
    • Feature engineering
    • Model evaluation and validation
  • Experience with common ML/data libraries (e.g., pandas, NumPy, scikitlearn, or similar)
  • Experience with AI Tools like Copilot, Copilot GitHub etc.
  • Ability to work independently, take initiative, and operate effectively in ambiguous problem spaces
  • Strong analytical thinking and communication skills

Preferred Qualifications

  • Handson experience with endtoend ML projects, including experimentation and evaluation
  • Familiarity with Databricks or similar data/ML platforms
  • Exposure to cloudbased ML workflows (Azure preferred)
  • Experience with deep learning or NLP frameworks (e.g., PyTorch, TensorFlow, Hugging Face)
  • Working knowledge of Generative AI or LLMs as an applied technique (not required)
  • Prior internship, research, or applied ML project experience with measurable outcomes

What You'll Gain

  • Ownership of real machine learning experiments with direct business visibility
  • Experience working in a startuplike, experimentdriven environment inside a large enterprise
  • Handson exposure to enterprisescale data and ML workflows using Databricks and Microsoft platforms
  • Mentorship from experienced AI and Emerging Technology leaders
  • Strong preparation for fulltime roles in Machine Learning Engineering, Applied Data Science, or AI Engineering

Salary Target Range: $28/hr-$30/hr 

Rust-Oleum is an equal opportunity employer. Employment selection and related decisions are made without regard to sex, race, age, disability, religion, national origin, color, or any other protected class.

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