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Director Machine Learning Jobs in Chicago, IL (NOW HIRING)

Ownership of real machine learning experiments with direct business visibility * Experience working in a startuplike, experimentdriven environment inside a large enterprise * Handson exposure to ...

Machine Learning Engineer

Chicago, IL · On-site

$160K - $220K/yr

Coinflow is seeking a Machine Learning Engineer to help build the intelligence layer that powers ... Direct impact on core risk infrastructure and company trajectory during a hypergrowth phase The ...

Machine Learning Engineer

Chicago, IL · On-site

$160K - $220K/yr

Coinflow is seeking a Machine Learning Engineer to help build the intelligence layer that powers ... Direct impact on core risk infrastructure and company trajectory during a hypergrowth phase The ...

Ontrac Solutions is seeking Machine Learning Engineers to support an urgent staff augmentation ... The selected engineers will work under the direct guidance of a Staff ML Architect and will focus ...

Ontrac Solutions is seeking Machine Learning Engineers to support an urgent staff augmentation ... The selected engineers will work under the direct guidance of a Staff ML Architect and will focus ...

Hands-on experience applying machine learning and deep learning to vision data, preferably direct experience with TensorFlow (preferred), Caffe, Keras, Theano or Torch * Excellent verbal and written ...

Principal Machine Learning Engineer At IMC, we believe technology is the foundation of our ... Direct impact on trading -- Your infrastructure will power models that make real trading decisions ...

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Showing results 1-20

Director Machine Learning information

See Chicago, IL salary details

$37.1K

$94.7K

$145.3K

How much do director machine learning jobs pay per year?

As of May 28, 2026, the average yearly pay for director machine learning in Chicago, IL is $94,704.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,700.00 and $109,200.00 per year, depending on experience, location, and employer.

What is a Director Machine Learning job?

A Director of Machine Learning leads teams in developing and deploying machine learning models to solve business challenges. They define the AI strategy, oversee research, and ensure models are scalable and ethical. This role requires expertise in machine learning, data science, and leadership, as well as collaboration with cross-functional teams. Directors also stay updated on industry advancements and drive innovation within their organizations.

What are the key skills and qualifications needed to thrive in the Director Machine Learning position, and why are they important?

To thrive as a Director Machine Learning, you need advanced expertise in machine learning, statistics, data science, and leadership, typically supported by a master's or Ph.D. in a related field and several years of relevant industry experience. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and data management systems, as well as certifications like AWS Certified Machine Learning or Google Professional Machine Learning Engineer, are commonly required. Exceptional communication, strategic thinking, and team management skills distinguish top candidates in this role. These capabilities are essential for driving organizational AI initiatives, fostering high-performing teams, and delivering impactful business solutions.

What are the primary responsibilities and challenges faced by a Director of Machine Learning on a daily basis?

A Director of Machine Learning is typically responsible for overseeing the development and deployment of machine learning solutions, mentoring technical teams, setting strategic direction for AI initiatives, and ensuring the alignment of projects with organizational goals. Challenges often include balancing innovative research with business priorities, navigating evolving technology landscapes, and coordinating efforts across data science, engineering, and stakeholder teams. This role requires regular collaboration with product managers, executives, and cross-functional departments to prioritize initiatives and communicate complex technical concepts. Successful directors excel at fostering a culture of continuous learning, optimizing team productivity, and staying ahead in a fast-paced, rapidly changing field.
What are the most commonly searched types of Machine Learning jobs in Chicago, IL? The most popular types of Machine Learning jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Director Machine Learning jobs? Cities near Chicago, IL with the most Director Machine Learning job openings:
Infographic showing various Director Machine Learning job openings in Chicago, IL as of May 2026, with employment types broken down into 76% Full Time, 13% Contract, and 11% Nights. Highlights an 85% In-person, and 15% Remote job distribution, with an average salary of $94,704 per year, or $45.5 per hour.
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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