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Machine Learning Engineer Jobs in Des Plaines, IL

Crowe

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 ...

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 ...

Crowe

Machine Learning Engineer

Chicago, IL

$29.81 - $48.08/hr

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 ...

Crowe Advisory LLC

Machine Learning Engineer

Chicago, IL · On-site

$80 - $100/hr

About the Role 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 ...

Lightspeed

AI & Machine Learning Engineer

Northbrook, IL · On-site

$100 - $125/hr

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems that make LightSpeed's construction robots smarter, faster, and more autonomous. You will develop ...

Bespoke Labs

Machine Learning Engineer

Chicago, IL

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Aurora, IL · On-site

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Bespoke Labs

Machine Learning Engineer

Aurora, IL

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Des Plaines, IL

Machine Learning Engineer information

See Des Plaines, IL salary details

$30.7K

$125.5K

$188.6K

How much do machine learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning engineer in Des Plaines, IL is $125,483.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,900.00 and $151,000.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

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The top searched job categories for Machine Learning Engineer jobs in Des Plaines, IL are:

What cities near Des Plaines, IL are hiring for Machine Learning Engineer jobs?

Cities near Des Plaines, IL with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Des Plaines, IL as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 25% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $125,483 per year, or $60.3 per hour.

Machine Learning Engineer

Chicago, IL • On-site

Techgroup America Inc.
1 - 10 employees
Learn more about Techgroup America Inc.external

Other

Posted 4 days ago

Job description

Role:- Machine Learning Engineer
Location:- Hybrid at Chicago, IL

  • There is an ML model they built to predict their account balances.
  • It is potentially ready to be used for income simulation forecasting that has been manual and now they can automate and use this model as a potential input.
  • If the model is accurate enough and they can explain it well enough they can push this.
  • This is a lot more about technical expertise and technical leadership than strategic. More Engineer.
  • AWS Sagemaker. Switching from AWS to Databricks. Expertise in more than one tool is helpful. AWS and Databricks. LLM. Cloud formation Lambda. Python. Pyspark AWS Glue. ML Ops Sagemaker.
  • We had a very strong profile submitted that the team really liked, but they identified a candidate another candidate with more hands on keyboard experience in ML Ops in Sagemaker.
  • More senior, experienced ML Engineer that has built similar models and is familiar with other tech ologies, including AWS SageMaker and Databricks (currently using AWS Forecast), Jupyter Notebook, AWS Bedrock, XGBoost.
  • AWS Suite
  • Python
  • Amazon ECR
  • Version Control
  • Integration with ADO
  • Building, enhancing, explaining, risk and audit experience to understand controls.
  • Looking at model optimization and metrics and importance. How to incrementally improve those. Getting the optimized version. Good stakeholder engagement experience.
  • Data ingestion: RDS database, SQL Server, FRED Data (Federal Reserve Economic Data), MSRP . org (Municipal Securities Rulemaking Board).
  • Onsite Tuesday and Thursday ideally, but they can be flexible if someone wants other days.

Job Description - Duties:

  • Collaborate with data scientists, software engineers, and DevOps teams to develop and deploy ML models
  • Build, test, and deploy ML Ops pipelines on AWS
  • Manage and monitor production ML systems to ensure optimal performance, reliability, and scalability
  • Design and implement automated workflows for data cleaning, feature engineering, model training, and model deployment
  • Develop and maintain documentation for ML Ops processes and procedures
  • Continuously improve ML Ops pipeline performance and efficiency
  • Troubleshoot and resolve issues related to ML model performance, data quality, and infrastructure
 
Requirements:
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field
  • Minimum of 5-7 years of experience in ML Ops, DevOps, or related roles
  • Strong knowledge of AWS services and tools related to ML Ops, such as SageMaker, Step Functions, Lambda, and CloudFormation
  • Hands-on experience building and deploying ML models in production using AWS
  • Proficiency in Python and/or other programming languages commonly used in ML, such as R, Java, or Scala
  • Familiarity with containerization technologies such as Docker and Kubernetes
  • Excellent problem-solving skills and attention to detail
  • Ability to work independently as well as in a team environment
  • Strong communication skills and ability to explain technical concepts to non-technical stakeholders
 
Knowledge, Skills, Abilities and Behaviors:
  • Knowledge of machine learning concepts, algorithms, and frameworks.
  • Knowledge of software engineering principles and best practices, such as version control, continuous integration, and agile development methodologies.
  • Strong understanding of data analysis and data manipulation techniques.
  • Ability to design and implement scalable, secure, and fault-tolerant ML Ops pipelines on AWS.
  • Ability to analyze and interpret data to identify patterns, trends, and anomalies, using advanced data manipulation techniques.
  • Outstanding communication skills (verbal, written, visualization, and listening).
  • Self-starter who can work independently as well as in a team setting.
  • Hands-on technologist with the ability to help drive the strategy and mentor others.
  • Giving and receiving effective feedback across all interactions.
  • Interest in understanding customer perspectives to aid in the development of the right solution.
  • Interest in understanding business needs to aid in developing solutions that are right for the broader organization.

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