1

Contract Junior Machine Learning Engineer Jobs in Chicago, IL

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 ...

Machine Learning Engineer

Chicago, IL ยท On-site

$95K - $138K/yr

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 ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Machine Learning Engineer

Chicago, IL ยท On-site

$100 - $125/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 ...

Our machine learning engineering team is responsible for developing infrastructure and tooling to help enable data driven decisions and insights at scale for millions of Paylocity users. As a Staff ...

Senior Machine Learning Engineer

Schaumburg, IL ยท 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 ...

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Lead Machine Learning Engineer

Chicago, IL ยท 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 ...

Lead Machine Learning Engineer

Chicago, IL ยท 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 ...

Lead Machine Learning Engineer

Chicago, IL ยท 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 ...

Lead Machine Learning Engineer

Chicago, IL ยท 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 ...

About the role Attain is seeking a Senior/Staff Machine Learning Engineer to own our production ML systems and build out the MLOps platform infrastructure that powers our suite of B2C financial ...

next page

Showing results 1-20

Contract Junior Machine Learning Engineer information

See Chicago, IL salary details

$34.5K

$74K

$112.8K

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

As of Sep 9, 2026, the average yearly pay for contract junior machine learning engineer in Chicago, IL is $73,964.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,000.00 and $82,400.00 per year, depending on experience, location, and employer.

What are the most commonly searched types of Junior Machine Learning Engineer jobs in Chicago, IL?

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

Infographic showing various Contract Junior Machine Learning Engineer job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $73,964 per year, or $35.6 per hour.

Machine Learning Engineer

Oakbrook Terrace, IL โ€ข On-site

Darwill, Inc.
Marketingย โ€ขย 201 - 500 employees

Full-time

Posted 15 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