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Full Time Machine Learning Data Annotation Jobs in Chicago, IL

IMC

Machine Learning Researcher

Chicago, IL

Design and deploy machine learning models to enhance trading performance across various asset ... Manage data acquisition, preprocessing, and feature engineering for structured and unstructured ...

IMC

Machine Learning Researcher

Chicago, IL · On-site

$250K - $300K/yr

Manage data acquisition, preprocessing, and feature engineering for structured and unstructured ... Base salary is only one component of total compensation; all full-time, permanent positions are ...

IMC

Machine Learning Research Lead

Chicago, IL · On-site

$250K - $300K/yr

Oversee data acquisition, preprocessing, and feature engineering for structured and unstructured ... Base salary is only one component of total compensation; all full-time, permanent positions are ...

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Showing results 21-40

All JobsMachine Learning Data Annotation JobsFull Time Machine Learning Data Annotation JobsFull Time Machine Learning Data Annotation Jobs in Chicago, IL

Full Time Machine Learning Data Annotation information

See Chicago, IL salary details

$38.6K

$126.4K

$202.4K

How much do full time machine learning data annotation jobs pay per year?

As of Aug 14, 2026, the average yearly pay for full time machine learning data annotation in Chicago, IL is $126,438.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $140,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a full time machine learning data annotation specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What is a full time machine learning data annotation job?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

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

The most popular types of Machine Learning Data Annotation jobs in Chicago, IL are:

What are popular job titles related to Full Time Machine Learning Data Annotation jobs in Chicago, IL?

For Full Time Machine Learning Data Annotation jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Full Time Machine Learning Data Annotation jobs in Chicago, IL look for?

The top searched job categories for Full Time Machine Learning Data Annotation jobs in Chicago, IL are:

Full Time Machine Learning Data Annotation jobs near you

Engineer II, Machine Learning Ops CBM Lab

Sralab

Chicago, IL

Full-time

Re-posted 25 days ago

Job description

Shirley Ryan AbilityLab is the global leader in physical medicine and rehabilitation for adults and children with the most severe, complex conditions. By joining our team, you'll be part of our life-changing mission and vision. You'll contribute to an innovative, multifaceted culture that is second to none - one that embraces collaboration, excellence, discovery and compassion. You'll play a role in something that's never been done before as we integrate science and clinical care to help patients achieve better, faster outcomes - as we Advance Human Ability, together.

Job Description Summary

The Machine Learning Ops Engineer II works under general supervision and plays an active role in the design, development, and/or operationalization of machine learning models. This position involves responsibility in planning and managing artificial intelligence (AI) and machine learning (ML) lifecycle processes and contributing to the efficiency and effectiveness of deployed models.
The Machine Learning Ops Engineer II will consistently demonstrate support of the Shirley Ryan AbilityLab statement of Vision, Mission and Core Values by striving for excellence, contributing to the team efforts and showing respect and compassion for patients and their families, fellow employees, and all others with whom there is contact at or in the interest of the institute.
The Machine Learning Ops Engineer II will demonstrate Shirley Ryan AbilityLab Core Attributes: Communication, Accountability, Flexibility/Adaptability, Judgment/Problem Solving, Customer Service and Core Values (Hope, Compassion, Discovery, Collaboration, and Commitment to Excellence) while fulfilling job duties.

Job Description

The Machine Learning Engineer II will:

  • Actively participates in deploying, monitoring, and scaling machine learning models in production and big data research.

  • Evaluate data sets to determine suitability for applying machine learning models and techniques.

  • Guide and assist with the collection and curation of clinical datasets.

  • Assist in the implementation and evaluation of machine learning algorithms.

  • Develop and maintain continuous integration and continuous deployment pipelines for automated training and deployment of machine learning models.

  • Manage machine learning infrastructure and optimizes resource utilization.

  • Implement monitoring solutions for model performance and health.

  • Lead small projects or initiatives related to machine learning operations.

  • Work collaboratively with data scientists to optimize model performance.

  • Advocate for best practices in machine learning operations within the team.

  • Participate in maintaining a safe work environment through adherence to policies and procedures relative to safety, fire prevention, hazard communications, security, equipment use and maintenance, infection control and vehicle safety.

  • Perform all other duties that may be assigned in the best interest of the Shirley Ryan AbilityLab.

Reporting Relationships:

  • Reports directly to a designed engineering manager.

Knowledge, Skills & Abilities Required

  • A professional level of knowledge in computer science, engineering or a related field, typically acquired through a Bachelor's Degree.

  • Minimum of 3 years of related experience working on problems of moderate scope where analysis of situations or data requires a review of a variety of factors.

  • Continues to develop professional expertise, applying institute policies and procedures to resolve a variety of issues.

  • Proficient in using version control systems, especially Git.

  • Able to manage branches, handle merge conflicts, and understand the importance of commit history and reverting changes.

  • Strong skills in Python and experience with machine learning frameworks.

  • Working proficiency with Linux and Windows operating systems.

  • Familiarity with tools for deploying machine learning pipelines (eg Docker, Kubenates).

  • Familiarity with cloud based production pipelines offered by leading manufacturers (eg Microsoft Azure, Amazon Web Services, Google Cloud, etc).

  • Ability to work independently on assigned tasks and lead small projects. Excellent problem-solving skills and the ability to troubleshoot complex issues.

  • Good communication skills in both written and verbal forms. Able to work with research subjects and clinicians in a clinical setting.

  • Able to take direction and complete defined tasks in addition to anticipating and executing follow-up actions.

  • Able to perform assignments by receiving general instructions on routine work, and detailed instructions on new projects or assignments.

  • Able to exercise judgment within defined procedures and practices to determine appropriate action.

  • Able to build stable working relationships with multidisciplinary team.

Working Conditions

  • Normal office environment with little or no exposure to dust or extreme temperature.

The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified.

Pay and Benefits*:

Pay Range:

$72,600.00 - $120,600.00

Benefits:

Shirley Ryan AbilityLab offers a comprehensive benefits program that is competitive with our industry peers in our geographic locations:https://www.sralab.org/benefits

*Benefits and benefits' eligibility can vary by position. Actual compensation will be determined by equity and qualifications of the role.

Equal Employment Opportunity Employer

Shirley Ryan AbilityLab is an Equal Employment Opportunity Employer. All applicants will be afforded equal employment opportunity without discrimination because of race, color, religion, sex, marital status, national origin or ancestry, citizenship status, age, disability, sexual orientation, gender identity, genetic information, military status, order of protection status, unfavorable discharge from military service, or any other characteristics protected by law.

EEO is the Law| EEO is the Law - Know Your Rights|View our Full Policy

Shirley Ryan AbilityLab is an Affirmative Action Employer as required by law.

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