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Full Time Machine Learning Data Annotation Jobs in Chicago, IL

Collaborate with senior engineers and data scientists on model deployment. * Conduct experiments and run machine learning tests. * Stay updated with the latest advancements in machine learning.

AI Project Manager

Chicago, IL · On-site

$53.25 - $72/hr

... agenda in large-scale data analytics and machine learning, as well as deliver innovative ... Full-time roles are eligible for bonuses and benefits. For additional information on Ryan Specialty ...

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/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

Schaumburg, IL · On-site

$120K - $159K/yr

Leverage cutting-edge big data technologies on AWS utilizing Databricks and Spark to develop scalable and efficient machine learning solutions for millions of users. * Create automated data and ...

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$150K - $185K/yr

This role will partner closely with data scientists, AI Technical Product Owners, and engineering teams to integrate machine learning capabilities into real business processes. The emphasis is on ...

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 ...

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

... machine learning, and AI models across key business areas such as credit, fraud, marketing, and ... It involves assessing model soundness, data quality, and performance to identify and mitigate model ...

Sr Machine Learning Engineer

Chicago, IL · On-site

$57.50 - $76/hr

... machine learning, and AI models across key business areas such as credit, fraud, marketing, and ... It involves assessing model soundness, data quality, and performance to identify and mitigate model ...

Machine Learning Engineer II

Chicago, IL · On-site

$100K - $137K/yr

Lessen's technology platform provides data-driven insights that unlock key growth opportunities for ... The Machine Learning Engineer II role is part of the Technology Team, which is responsible for ...

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Showing results 1-20

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 Jun 9, 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 are Full Time Machine Learning Data Annotation jobs?

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:
Machine Learning Engineer

Machine Learning Engineer

PayPal

Chicago, IL

Full-time

Medical, PTO

Posted 22 days ago


PayPal rating

6.8

Company rating: 6.8 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

15th of 17 rated payment service providers


Job description

The Company

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy.

We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers.

We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade.

Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do - and they push us to ensure we take care of ourselves, each other, and our communities.

Job Summary:

This job will validate and develop machine learning models and algorithms to solve complex problems. You will work closely with senior engineers, data scientists, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Job Description:

Essential Responsibilities:

  • Assist in the development and optimization of machine learning models.
  • Preprocess and analyze datasets to ensure data quality.
  • Collaborate with senior engineers and data scientists on model deployment.
  • Conduct experiments and run machine learning tests.
  • Stay updated with the latest advancements in machine learning.

Minimum Qualifications:

  • 1+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience.
  • Familiarity with ML frameworks like TensorFlow or scikit-learn.
  • Strong analytical and problem-solving skills.

Additional Responsibilities & Preferred Qualifications:

Role and Responsibilities

  • Support the lead of the team in performing oversight of high-impact statistical model and AI applications in a variety of business function areas, including but not limited to fraud detection, credit underwriting, marketing analytics etc.
  • Conduct quantitative and qualitative model validation according to Model Risk Management Policy to identify and understand model risk issues
  • Collaborate with business units and model developers to remediate model issues and provide subject-matter expert opinion on model improvements
  • Perform model and AI risk governance related activities in line with enterprise risk framework, to ensure PayPal's AI applications are compliant with ever evolving regulatory expectation such as Responsible AI.

Qualifications

This position requires the ability and curiosity to learn various advanced modeling methods/AI techniques, covering a broader business function. This role also requires candidate to have the capability in building effective relationship with various stakeholders including business owners, model owners, model developers and control officers. The candidate must possess excellent communication, writing and presentation skills.

  • An advanced degree in a quantitative field, such as statistics, mathematics, computer science or engineering essential
  • Advanced knowledge of statistical and machine learning models (e.g., logistic regression, time series analysis, random forests, SVMs, XGBoost,CNNs/RNNs)
  • Possessing advanced coding skills in dealing with big data (e.g.,Scikit-learn inPython,Tensorflow, Hadoop,Spark, SQL, etc.)
  • Relevant Modeling experience in credit scoring, fraud detection, financial forecasting, or marketing analytics obtained either in academic or financial industry
  • Ability to work effectively both independently and in a team environment
  • Ability to communicate effectively and establish constructive relationship with stakeholders

Subsidiary:

PayPal

Travel Percent:

0

-

The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is:

Primary Location | Pay Range:

Chicago, Illinois | ($117,500.00 - $174,350.00 Annually)

Additional Location(s) | Pay Range:

Austin, Texas | ($117,500.00 - $174,350.00 Annually) Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.

PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing-physical, emotional, and financial-delivering meaningful value where it matters most.We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.

Who We Are:

Click Here to learn more about our culture and community.

Commitment to Diversity and Inclusion

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.

Belonging at PayPal:

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please Join our Talent Community.

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don't hesitate to apply.


What PayPal employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


PayPal logo

About PayPal

Sourced by ZipRecruiter

PayPal has remained at the forefront of the digital payment revolution for more than 20 years. By leveraging technology to make financial services and commerce more convenient, affordable, and secure, the PayPal platform is empowering more than 400 million consumers and merchants in more than 200 markets to join and thrive in the global economy. For more information, visit paypal.com. PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1998

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