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Machine Learning Engineer Apprenticeship Jobs in Lombard, IL

Moody

Machine Learning Engineer

Chicago, IL · On-site

$96 - $139/hr

Machine Learning Engineer (14907) At Moody's, we unite the brightest minds to turn today's risks into tomorrow's opportunities. We do this by striving to create an inclusive environment where ...

New

Qfanalytics

Machine Learning Engineer

Chicago, IL · On-site

$80 - $120/hr

Preferred Qualifications PhD in Mathematics, Engineering, Physics or related field; 4-8 years experience working in Machine Learning; Experience with deep learning frameworks like TensorFlow or ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning Engineering organization! Our machine learning engineering team is responsible for developing ...

Capital One

Lead Machine Learning Engineer

Chicago, IL · On-site

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Chicago, IL · On-site +1

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Socket.dev

Lead Machine Learning Engineer

Chicago, IL · On-site

$179 - $205/hr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Chicago, IL · On-site

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Chicago, IL · On-site +1

$105K - $139K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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All JobsMachine Learning Engineer Apprenticeship JobsMachine Learning Engineer Apprenticeship Jobs in Lombard, IL

Machine Learning Engineer Apprenticeship information

See Lombard, IL salary details

$30K

$67.5K

$113.7K

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

As of Sep 3, 2026, the average yearly pay for machine learning engineer apprenticeship in Lombard, IL is $67,525.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,200.00 and $73,300.00 per year, depending on experience, location, and employer.

What is a machine learning engineer apprenticeship?

A Machine Learning Engineer Apprenticeship is a structured training program that combines hands-on work experience with classroom or online learning in the field of machine learning. Apprentices work under the guidance of experienced professionals to develop skills in data analysis, building machine learning models, and deploying algorithms in real-world applications. This apprenticeship is ideal for individuals seeking to enter the field of artificial intelligence without prior extensive experience, as it provides practical training and mentorship. Typically, apprenticeships last from several months to a couple of years and may lead to full-time employment upon successful completion.

What types of projects can I expect to work on during a machine learning engineer apprenticeship?

As a Machine Learning Engineer Apprentice, you can expect to participate in hands-on projects that involve data preprocessing, building and evaluating machine learning models, and collaborating with cross-functional teams such as data scientists and software engineers. Common projects may include developing recommendation systems, automating data analysis tasks, or implementing natural language processing solutions. These experiences provide valuable exposure to real-world datasets and industry-standard tools, helping you build foundational skills for a long-term career in machine learning.

What are the key skills and qualifications needed to thrive as a machine learning engineer apprentice, and why are they important?

To thrive as a Machine Learning Engineer Apprentice, a solid understanding of mathematics, programming (especially Python), and foundational machine learning concepts is essential, often supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is typically required. Strong analytical thinking, attention to detail, and the ability to collaborate and communicate complex ideas clearly are valuable soft skills. These abilities are crucial for efficiently developing, testing, and deploying machine learning models while contributing effectively to team projects.

What are popular job titles related to Machine Learning Engineer Apprenticeship jobs in Lombard, IL?

For Machine Learning Engineer Apprenticeship jobs in Lombard, IL, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Apprenticeship jobs in Lombard, IL look for?

The top searched job categories for Machine Learning Engineer Apprenticeship jobs in Lombard, IL are:

What cities near Lombard, IL are hiring for Machine Learning Engineer Apprenticeship jobs?

Cities near Lombard, IL with the most Machine Learning Engineer Apprenticeship job openings:

Machine Learning Engineer Apprenticeship jobs near you
Infographic showing various Machine Learning Engineer Apprenticeship job openings in Lombard, IL as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $67,525 per year, or $32.5 per hour.

Machine Learning Engineer

Darwill, Inc.

Oakbrook Terrace, IL • On-site

Full-time

Posted 9 days ago

Job description

Overview
Darwill is a nationally recognized print and marketing communications firm based in the west suburbs of Chicago. As a premier provider of complex, data-driven marketing solutions, we help CMOs and marketing leaders drive measurable performance through advanced analytics, automation, and AI-powered insights.
We are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional machine learning models (e.g., propensity and segmentation models) while also building and maintaining the core data pipelines on Databricks that power our analytics and modeling platforms.
This role is intentionally scoped for a mid-level engineer: someone with enough experience to work independently and make sound engineering decisions, but who is still hands-on, execution-focused, and eager to grow. This is not an entry-level position, and it is not a principal or architect-level role.
Location
Chicago, IL area (Oak Brook / West Suburbs)
Hybrid work model with 1-2 days onsite per week required
Reports To
VP of Data Engineering & Data Science
Responsibilities / Essential Functions
Data Engineering & Platform Foundations
  • Design, build, and maintain ETL pipelines in Databricks using Spark and Delta Lake
  • Independently implement data transformations, joins, and aggregations across large, multi-source datasets
  • Build and maintain data validation and quality checks to ensure reliability of downstream analytics and ML workflows
  • Optimize Databricks jobs for performance, scalability, and cost efficiency
  • Write and maintain clear technical documentation for data pipelines and tables

ML Engineering & MLOps
  • Partner closely with Data Scientists to support traditional ML model development, including feature engineering, training, validation, and deployment
  • Productionize propensity, ranking, and segmentation models used in large-scale marketing campaigns
  • Build and maintain repeatable ML pipelines for training, batch scoring, and inference
  • Implement model versioning, experiment tracking, and reproducibility standards
  • Support model performance monitoring, drift detection, and retraining cycles

Deployment, Monitoring & Operations
  • Deploy data pipelines and ML workflows into production environments serving millions of records
  • Implement monitoring and alerting for data and ML pipelines
  • Support A/B testing and model performance evaluation in partnership with Data Science
  • Troubleshoot production issues independently and collaborate effectively when escalation is needed

GenAI (Secondary / Directional)
  • Contribute to GenAI initiatives as capacity allows
  • Stay informed on emerging AI technologies and tooling
  • (GenAI is not the primary focus of this role today.)

Required Qualifications
Experience
  • 3-6 years of professional experience in machine learning engineering, data engineering, or a closely related role
  • Experience working in production environments with minimal day-to-day supervision
  • Demonstrated ability to collaborate effectively with Data Scientists and translate models into production systems

Technical Skills (Must-Have)
Data Engineering & Platform
  • Apache Spark (PySpark, SparkSQL)
  • Databricks (ETL pipelines, workflows, Delta Lake)
  • Strong SQL skills (complex queries, joins, window functions, optimization)
  • Experience building and maintaining scalable data pipelines

Programming & Machine Learning
  • Python (pandas, numpy, scikit-learn; experience with XGBoost or LightGBM preferred)
  • Feature engineering and data preparation for ML models
  • Working knowledge of supervised learning models (classification, regression, ranking)

MLOps & Production
  • Experience deploying ML models into production
  • Model versioning and experiment tracking (e.g., MLflow or similar)
  • Monitoring data quality and model performance in production
  • Supporting retraining and validation workflows

Cloud & Tooling
  • Experience with a major cloud platform (Databrick, AWS)
  • Familiarity with workflow orchestration tools (Databricks Workflows or similar)

Preferred Qualifications (Nice-to-Have)
  • Experience with propensity modeling, customer segmentation, or marketing analytics
  • Exposure to CI/CD concepts for data and ML pipelines
  • Experience with Docker or containerized deployments
  • Exposure to GenAI, LLMs, or RAG-based systems
  • Master's degree in Computer Science, Statistics, or a related field
  • Seniority Level
    Associate
  • Industry
    • Marketing Services
  • Employment Type
    Full-time
  • Job Functions

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