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Machine Learning Testing Jobs in Illinois (NOW HIRING)

Darwill

Machine Learning Engineer

Villa Park, IL · Hybrid

MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING) Overview Darwill is a nationally recognized ... Support A/B testing and model performance evaluation in partnership with Data Science

Aquabyte

Machine Learning Engineer

Mundelein, IL · On-site

Aquabyte is seeking a Machine Learning Engineer to help develop and deploy new algorithms to fish ... Strong software engineering skills; knowledge of best practices, testing, and deployment Bonus ...

Allied

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$150K - $185K/yr

POSITION SUMMARY The Senior Machine Learning Engineer is responsible for designing, building, and ... Understanding of MLOps concepts including model versioning, monitoring, testing, and lifecycle ...

Capital One

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$107.60K - $147.80K/yr

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... Solve complex problems by writing and testing application code, developing and validating ML models ...

Kasmo Global

Sr. Machine Learning Engineer

Schaumburg, IL · On-site

$103K - $141.40K/yr

Toyota Connected's Mobility team is looking for a Sr. Machine Learning Engineer who will use ... Developing CI/CD pipelines, unit and functional testing * Establishing model monitoring and model ...

IMC

Hardware Machine Learning Engineer

Chicago, IL

$127.20K - $167.90K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

IMC Inc

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

Hardware Machine Learning Engineer Chicago, United States; New York, United States We are deploying ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

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How much do machine learning testing jobs pay per hour?

As of May 28, 2026, the average hourly pay for machine learning testing in Illinois is $22.11, according to ZipRecruiter salary data. Most workers in this role earn between $19.09 and $24.71 per hour, depending on experience, location, and employer.

What is a Machine Learning Testing job?

A Machine Learning Testing job involves evaluating and validating machine learning models to ensure they function correctly, efficiently, and ethically. This includes testing for accuracy, reliability, bias, and performance under different conditions. Professionals in this role employ techniques such as unit testing, integration testing, data validation, and model performance monitoring. They also work closely with data scientists and engineers to debug issues and improve model robustness. The goal is to ensure that machine learning systems perform as expected and meet business or regulatory requirements.

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

To excel in Machine Learning Testing, you need a solid understanding of machine learning concepts, data analysis, and programming skills in languages like Python, as well as a background in quality assurance or software testing. Familiarity with frameworks such as TensorFlow, PyTorch, automated testing tools, and relevant certifications like ISTQB are highly beneficial. Strong attention to detail, analytical thinking, and effective communication skills help testers identify issues and collaborate with data scientists and developers. These competencies are essential to ensure the reliability, fairness, and accuracy of machine learning models deployed in production environments.

What are the typical challenges faced by professionals in Machine Learning Testing roles?

Professionals in Machine Learning Testing often encounter challenges such as dealing with non-deterministic model outputs, insufficient or imbalanced datasets, and unclear or evolving testing criteria. They may need to work closely with data scientists and engineers to develop robust test cases and validation methods tailored for dynamic machine learning systems. Staying updated on advancements in testing methodologies and tools is also important, as the field evolves rapidly. Successfully overcoming these challenges leads to higher quality models and more reliable AI solutions for end users.
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What are the most commonly searched types of Machine Learning Testing jobs in Illinois? The most popular types of Machine Learning Testing jobs in Illinois are:
What are popular job titles related to Machine Learning Testing jobs in Illinois? For Machine Learning Testing jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Machine Learning Testing jobs in Illinois look for? The top searched job categories for Machine Learning Testing jobs in Illinois are:
Machine Learning Testing jobs near you
Infographic showing various Machine Learning Testing job openings in Illinois as of May 2026, with employment types broken down into 3% As Needed, 80% Full Time, 13% Part Time, 3% Contract, and 1% Nights. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $45,998 per year, or $22.1 per hour.
Machine Learning Engineer

Machine Learning Engineer

Darwill, Inc.

Oakbrook Terrace, IL • On-site

Full-time

Posted 7 days ago

Job description

MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING)
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

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