Machine Learning Co-Op, Jan - Aug 27'

Co‑Op Student – Machine Learning & Applied AI

Location

Hybrid – Minimum 3 days per week on‑site (Vernon Hills, IL)

Duration

Co‑Op Term (6–8 months) January 2027 - August 2027

Department

Automation & Emerging Technology

Reports To

Emerging Technologies Leader

Candidate Level

Bachelor’s, Master’s, or PhD‑track students

Position Overview

We are seeking a highly motivated Machine Learning & Applied AI Co‑Op Student to join our Automation & Emerging Technology team. This role is ideal for students who want hands‑on ownership of real‑world machine learning experiments in a fast‑moving, startup‑like environment within a large enterprise.

The co‑op will focus on applied machine learning, data‑driven experimentation, and model evaluation, with opportunities to explore Generative AI and large language models where they meaningfully support ML‑driven 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 on‑site at our Vernon Hills, IL office.

Key Responsibilities

• Lead machine learning experiments end‑to‑end, 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 PhD‑track program in Computer Science, Data Science, Machine Learning, Statistics, or a related field
• Ability to work on‑site 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, scikit‑learn, 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

• Hands‑on experience with end‑to‑end ML projects, including experimentation and evaluation
• Familiarity with Databricks or similar data/ML platforms
• Exposure to cloud‑based 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 startup‑like, experiment‑driven environment inside a large enterprise
• Hands‑on exposure to enterprise‑scale data and ML workflows using Databricks and Microsoft platforms
• Mentorship from experienced AI and Emerging Technology leaders
• Strong preparation for full‑time 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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