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Full Time Machine Learning Compiler Engineer Jobs in Chicago, IL

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120.90K - $159.40K/yr

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 Senior ...

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 deploying scalable machine learning systems that drive business impact. This role will partner ...

Sr. Machine Learning Engineer

Chicago, IL · Remote

$107.60K - $147.80K/yr

Who we are looking for We're seeking a Sr Machine Learning Engineer to play a critical role in ... Regular full-time employees are eligible for benefits - see here. #LI-KB1

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques, including but ...

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field. * Strong knowledge of statistical and machine learning techniques, including but ...

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Full Time Machine Learning Compiler Engineer information

See Chicago, IL salary details

$32.5K

$132.7K

$199.3K

How much do full time machine learning compiler engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for full time machine learning compiler engineer in Chicago, IL is $132,651.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $159,700.00 per year, depending on experience, location, and employer.

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

AspectFull Time Machine Learning Compiler EngineerData Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related; strong programming and analytical skills
Work EnvironmentSoftware development teams, focusing on compiler optimization and ML infrastructureData analysis teams, focusing on data modeling, visualization, and insights
Industry UsageTech companies, AI startups, hardware firmsFinance, healthcare, marketing, and tech sectors

The Full Time Machine Learning Compiler Engineer primarily develops and optimizes compilers for ML models, requiring deep technical knowledge of compiler architecture. In contrast, Data Scientists analyze data to generate insights and build models without focusing on compiler development. Both roles are essential in AI-driven industries but serve different technical and business functions.

What are the most commonly searched types of Machine Learning Compiler Engineer jobs in Chicago, IL? The most popular types of Machine Learning Compiler Engineer jobs in Chicago, IL are:

$53 - $72.75/hr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 19 days ago


Reyes Coca-Cola Bottling rating

8.1

Company rating: 8.1 out of 10

Based on 94 frontline employees who took The Breakroom Quiz

67th of 378 rated food and drinks producers


Job description

Position Responsibilities: 

  • Design, build, and maintain Continuous Integration/Continuous Development (CI/CD) pipelines for machine learning models 
  • Deploy and manage ML models in production environments using containerization and orchestration technologies 
  • Implement monitoring, logging, and alerting solutions to track model performance, system health, and data drift 
  • Collaborate with data scientists to understand model requirements and optimize the process of transforming models from development to a production-ready state 
  • Create and maintain technical documentation for ML Operations (Ops) processes, infrastructure, and deployments 
  • Define ML/Artificial Intelligence (AI) governance to ensure data security and ethical standards are met for all modeling processes 
  • Travel up to 5% of the time 
  • Other duties as assigned  

Required Education and Experience: 

  • Bachelor’s degree in computer science, Data Science, Mathematics, or related quantitative discipline and 3 to 5 plus years of experience in ML Engineering, Software Engineering, or a related field or High School Diploma/General Education Diploma and 7 plus years of the above stated experience 

Preferred Education and Experience: 

  • Master’s Degree in computer science, Data Science, or other graduate education in related quantitative fields 
  • Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML development lifecycle 
  • Experience building ML Ops infrastructure and serving models via cloud platforms such as Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP) 
  • Strong proficiency in Python and working knowledge of Bash/shell scripting for automation and system operations 
  • Strong understanding of Structured Query Language (SQL) and experience with big data platforms, i.e., Snowflake, Databricks, or similar 
  • Experience with Infrastructure-as-Code tools, i.e., Terraform, Azure Resource Manager, or similar

Benefits
At the Reyes Family of Businesses, our Total Rewards Strategy prioritizes the holistic well-being of our employees. This position offers a comprehensive benefits package that includes Medical, Dental, Vision coverage, Paid Time Off, Retirement Benefits, and complimentary Health Screenings.
Equal Opportunity Employee & Physical Demands
Reyes Holdings and its businesses are equal opportunity employers. Company policy prohibits discrimination and harassment against any applicant or employee based on race, color, religion, sex, pregnancy or pregnancy-related medical conditions, marital status, sexual orientation, gender identity or expression, age, national origin, citizenship, disability, genetic information, military or veteran status, or any other basis protected by applicable law. In addition, the Company is committed to providing reasonable accommodation to applicants and employees in accordance with applicable law. Requests for accommodation should be directed to your point of contact in the Talent Acquisition or Human Resources departments.
Background Check and Drug Screening
Offers of employment are contingent upon successful completion of a background check and drug screening.
Pay Transparency
Our compensation philosophy embraces diverse factors for fair pay decisions, valuing skills, experience, and the needs of our business. Moreover, this role may have the opportunity to participate in a discretionary incentive program, subject to program rules.Qualifications:

Required Education and Experience: 

  • Bachelor’s degree in computer science, Data Science, Mathematics, or related quantitative discipline and 3 to 5 plus years of experience in ML Engineering, Software Engineering, or a related field or High School Diploma/General Education Diploma and 7 plus years of the above stated experience 

Preferred Education and Experience: 

  • Master’s Degree in computer science, Data Science, or other graduate education in related quantitative fields 
  • Hands-on experience with CI/CD pipelines, automation tools, and version control systems like Azure DevOps, Github, or similar and strong understanding of machine learning concepts and the ML development lifecycle 
  • Experience building ML Ops infrastructure and serving models via cloud platforms such as Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP) 
  • Strong proficiency in Python and working knowledge of Bash/shell scripting for automation and system operations 
  • Strong understanding of Structured Query Language (SQL) and experience with big data platforms, i.e., Snowflake, Databricks, or similar 
  • Experience with Infrastructure-as-Code tools, i.e., Terraform, Azure Resource Manager, or similar
Education:UNAVAILABLEEmployment Type: FULL_TIME

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