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Junior Machine Learning Engineer Jobs in Naperville, IL

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 ...

Moody's Corporation

Machine Learning Engineer

Chicago, IL

$95K - $138K/yr

Expertise in Python programming, including machine learning libraries such as NumPy, Pandas, and PyTorch * Experience with machine learning operations practices, including continuous integration and ...

New

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 ...

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 ...

The Hartford

Senior AI Machine Learning Engineer

Chicago, IL · Hybrid

$126K - $166K/yr

As a Senior Machine Learning Engineer , you will play a critical role in designing, building, and ... Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable ...

Apex Systems

Senior Machine Learning Engineer

Chicago, IL · On-site

$107K - $147K/yr

Hyatt seeks an extraordinary Machine Learning Engineer to help build the algorithmic assets and features that Hyatt guests, members, customers and internal users leverage to transform the guest ...

Crowe LLP

Machine Learning Engineer

Chicago, IL · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

The Hartford

Sr AI Machine Learning Engineer

Chicago, IL · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations ... Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable ...

The Hartford

Sr AI Machine Learning Engineer

Chicago, IL · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations ... Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable ...

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Naperville, IL

Junior Machine Learning Engineer information

See Naperville, IL salary details

$33.2K

$71.2K

$108.6K

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

As of Aug 31, 2026, the average yearly pay for junior machine learning engineer in Naperville, IL is $71,183.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,100.00 and $79,300.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
More about Junior Machine Learning Engineer jobs

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The most popular types of Machine Learning Engineer jobs in Naperville, IL are:

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

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Cities near Naperville, IL with the most Junior Machine Learning Engineer job openings:

Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Naperville, IL as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $71,183 per year, or $34.2 per hour.

Machine Learning Engineer

Darwill, Inc.

Oakbrook Terrace, IL • On-site

Full-time

Posted 6 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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