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Machine Learning Engineer Jobs in Wheeling, IL (NOW HIRING)

IMC Trading

Machine Learning Researcher

Chicago, IL · On-site

The role involves designing and deploying machine learning models, collaborating with trading teams ... Required : • PhD or Master's in Engineering, Math, Statistics, Computer Science, or related ...

Meta

Software Engineer, Machine Learning

Chicago, IL

$183K/yr

Software Engineer, Machine Learning Responsibilities: * Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences * Implement ...

IMC

Machine Learning Researcher

Chicago, IL

... machine learning & deep learning to solve challenging trading problems. This role is part of a ... The ideal candidate will have experience working with other researchers and engineers to build and ...

Varsity Tutors

Machine Learning Tutor

Evanston, IL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Highland Park, IL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Chicago, IL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Schaumburg, IL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Des Plaines, IL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Wheaton, IL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Skokie, IL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Buffalo Grove, IL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Lake Forest, IL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Wheeling, IL

Machine Learning Engineer information

See Wheeling, IL salary details

$32.6K

$133.3K

$200.3K

How much do machine learning engineer jobs pay per year?

As of Jul 21, 2026, the average yearly pay for machine learning engineer in Wheeling, IL is $133,324.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,100.00 and $160,500.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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 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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Wheeling, IL? The most popular types of Machine Learning Engineer jobs in Wheeling, IL are:
What job categories do people searching Machine Learning Engineer jobs in Wheeling, IL look for? The top searched job categories for Machine Learning Engineer jobs in Wheeling, IL are:
What cities near Wheeling, IL are hiring for Machine Learning Engineer jobs? Cities near Wheeling, IL with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Wheeling, IL as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $133,324 per year, or $64.1 per hour.
Principal Architect - Machine Learning

Principal Architect - Machine Learning

United Airlines, Inc.

Chicago, IL • On-site

Full-time

Re-posted 18 days ago

United Airlines rating

7.8

Company rating: 7.8 out of 10

Based on 337 frontline employees who took The Breakroom Quiz

9th of 26 rated airlines

Job description

Description
United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions.
Job overview and responsibilities
United Airlines is seeking talented people to join the Data and Machine Learning Engineering team. The organization is responsible for leading data driven insights & innovation to support the Machine Learning needs for commercial and operational projects with a digital focus. This role will frequently collaborate with ML engineers, data scientists and data engineers. This role will design, architect, implement and lead key components of the Machine Learning Platform, Gen AI/ML business use cases, and establish processes and best practices.
  • Build high-performance, cloud-native machine learning infrastructure and services to enable rapid innovation across United
  • Set up containers and Serverless platform with cloud infrastructure
  • You will design and develop tools and apps to enable ML automation using AWS ecosystem
  • Build data pipelines to enable ML models for batch and real-time data
  • Hands on development expertise of Spark and Flink for both real time and batch applications
  • Support large scale model training and serving pipelines in distributed and scalable environment
  • Stay aligned with the latest developments in cloud-native and ML ops/engineering and to experiment with and learn new technologies - NumPy, data science packages like sci-kit, microservices architecture
  • Optimize, fine-tune generative AI/LLM models to improve performance and accuracy and deploy them
  • Evaluate the performance of LLM models, Implement LLMOps processes to manage the end-to-end lifecycle of large language models
  • Develop, optimize, fine-tune Generative AI/LLM models to improve performance and accuracy and deploy them

Qualifications
What's needed to succeed (Minimum Qualifications):
  • Bachelor's degree in
    Computer Science, Data Science, Generative AI, Engineering or related discipline or Mathematics experience required
  • 5+ years of software engineering experience with languages such as Python, Go, Java, or C/C++
  • 5+ years of experience in machine learning, deep learning, and natural language processing
  • Strong software engineering experience with Python and at least one additional language such as Go, Java, or C/C++
  • Strong technical leadership and familiarity with data science methodologies and frameworks (e.g., PyTorch, Tensorflow) and preferably building and deploying production ML pipelines
  • Experience in ML model life cycle development experience and prefer experience to common algorithms like XGBoost, CatBoost, Deep Learning, etc
  • Experience setting up and optimizing data stores (RDBMS/NoSQL) for production use in the ML app context
  • Cloud-native DevOps, CI/CD experience using tools such as Jenkins or AWS CodePipeline; preferably experience with GitOps using tools such as ArgoCD, Flux, or Jenkins X
  • Experience with generative models such as GANs, VAEs, and autoregressive models
  • Prompt engineering: Ability to design and craft prompts that evoke desired responses from LLMs
  • LLM evaluation: Ability to evaluate the performance of LLMs on a variety of tasks, including accuracy, fluency, creativity, and diversity
  • LLM debugging: Ability to identify and fix errors in LLMs, such as bias, factual errors, and logical inconsistencies
  • LLM deployment: Ability to deploy LLMs in production environments and ensure that they are reliable and secure
  • Experience with LLMOps (Large Language Model Operations) or AgenticOps (Agentic Operations) to manage the end-to-end lifecycle of large language models
  • Experience with generative ai methods such as retrieval augmented generation (RAG) and instruction fine tuning
  • Must be legally authorized to work in the United States for any employer without sponsorship
  • Successful completion of interview required to meet job qualification
  • Reliable, punctual attendance is an essential function of the position

What will help you propel from the pack (Preferred Qualifications):
  • Master's/PhD degree in
    Computer Science or related STEM field
  • 5 + years of experience working in cloud environments (AWS preferred) - Kubernetes, Dockers, ECS and EKS
  • 5 + years of experience with Big Data technologies such as Spark, Flink and SQL programming
  • 5 + years of experience with cloud-native DevOps, CI/CD
  • 3 - 5 + years of relevant enterprise Architecture experience
  • 1+ years of experience with Generative AI/LLMs

What United Airlines employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

United Airlines logo

About United Airlines

Sourced by ZipRecruiter

United Airlines is embarking on an exciting journey to become the best airline in aviation history. Our purpose, "Connecting People, Uniting the World," extends beyond transportation, emphasizing our commitment to uplift and create opportunities in the places we serve. With a global presence and diverse workforce, we value inclusivity and are dedicated to hiring tens of thousands of individuals across various roles. Our comprehensive benefits package, including perks like space available travel, parental leave, and 401k, aims to support your well-being and growth.

Industry

Aviation

Company size

10,000+ Employees

Headquarters location

Chicago, IL, US

Year founded

1926

Social media

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