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Freelance Machine Learning Data Annotation Jobs in Mount Prospect, IL

As a premier provider of complex, data-driven marketing solutions, we help CMOs and marketing ... We are seeking a Machine Learning Engineer (MLOps) to support the productionization of traditional ...

Oversee teams of data scientists, modelers, and ML engineers to deliver innovative and scalable ... Strategic Leadership and Vision Provide strategic direction for the organization's machine learning ...

Oversee teams of data scientists, modelers, and ML engineers to deliver innovative and scalable ... Strategic Leadership and Vision Provide strategic direction for the organization's machine learning ...

Machine Learning Lead

Chicago, IL · On-site

$225 - $275/hr

That means digging into large-scale transaction and behavioral data, shipping production fraud ... in machine learning, applied data science, or production ML roles * Demonstrated experience ...

Machine Learning Tutor

Wheaton, IL · Remote

$18 - $40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Showing results 21-40

Freelance Machine Learning Data Annotation information

See Mount Prospect, IL salary details

$12

$21

$34

How much do freelance machine learning data annotation jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for freelance machine learning data annotation in Mount Prospect, IL is $21.72, according to ZipRecruiter salary data. Most workers in this role earn between $17.21 and $24.86 per hour, depending on experience, location, and employer.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

Can I work for freelance machine learning data annotation with no experience?

Freelance machine learning data annotation jobs often do not require prior experience, as many tasks involve simple labeling or categorization that can be learned quickly. Basic computer skills, attention to detail, and familiarity with annotation tools are helpful, and training is usually provided. However, building a portfolio or gaining some familiarity with data annotation platforms can improve job prospects.

What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Mount Prospect, IL?

For Freelance Machine Learning Data Annotation jobs in Mount Prospect, IL, the most frequently searched job titles are:

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Mount Prospect, IL look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Mount Prospect, IL are:

What cities near Mount Prospect, IL are hiring for Freelance Machine Learning Data Annotation jobs?

Cities near Mount Prospect, IL with the most Freelance Machine Learning Data Annotation job openings:

Infographic showing various Freelance Machine Learning Data Annotation job openings in Mount Prospect, IL as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 17% Part Time, 1% Temporary, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $45,187 per year, or $21.7 per hour.

Machine Learning Engineer

Moody's Investors Service

Chicago, IL • On-site

$96 - $139/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago


Job description

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.


Employment eligibility to work in the U.S. is required, as Moody’s will not pursue visa sponsorship for this position

Skills and Competencies
  • Expertise in Python programming, including machine learning libraries such as NumPy, Pandas, and PyTorch
  • Experience with machine learning operations practices, including continuous integration and continuous deployment pipelines, model monitoring, and model maintenance preferred
  • Expertise with modern machine learning tools and platforms, including Jupyter, Docker, Git, and cloud computing environments such as Amazon Web Services or Google Cloud Platform
  • Experience building data tools for extract, transform, and load processes, extracting data from SQL and NoSQL databases, and conducting advanced data analysis
  • Experience with geographic information systems preferred
  • Excellent written and verbal communication skills, with the ability to understand and articulate business requirements and objectives to both technical and non-technical stakeholders
  • Expertise in supervised and unsupervised machine learning algorithms and their implementations, including advanced concepts such as active learning, computer vision, and deployments in complex environments
  • Deep expertise in artificial intelligence, with a track record of implementing advanced AI solutions to drive strategic transformation and operational efficiency. Strong experience using AI tools to lead innovation initiatives. Demonstrated leadership in managing AI-related risks, ensuring ethical governance, and fostering a culture of responsible AI adoption across the organization
Education
  • Advanced degree in a Science, Technology, Engineering, or Mathematics field required
  • Typically requires a minimum of two years of hands‑on industry experience in machine learning, computer vision, data science, or a related field
Responsibilities

Develop practical, scalable, and robust machine learning and computer vision solutions that enhance product capabilities and deliver value to clients.

  • Collect, clean, preprocess, and analyze data to support machine learning model development and maximize data value
  • Create visualizations and conduct exploratory analysis to identify patterns, trends, opportunities, and data quality issues
  • Train, evaluate, refine, and deploy machine learning models aligned with business objectives and product requirements
  • Design, implement, and automate large-scale model training, integration, and evaluation pipelines
  • Collaborate with machine learning, software engineering, product development, sales, and cross-functional stakeholders to deliver innovative solutions
  • Communicate technical findings and recommendations to both technical and non-technical audiences through clear documentation and presentations
  • Design and execute experiments to validate assumptions, improve model performance and support data-driven decision making
  • Ensure projects follow governance, security, ethical AI, and responsible data use practices while identifying and resolving operational inefficiencies
About the Team

Our Machine Learning Technology team is responsible for the core technology behind award-winning property intelligence solutions. We leverage machine learning, geospatial imagery, and computer vision to measure and monitor the built environment while delivering actionable insights to clients. By joining our team, you will contribute to innovative work that helps organizations better understand how homes and workplaces can withstand evolving climate and economic risks, while advancing the responsible adoption of artificial intelligence across our products and solutions.


For US-based roles only: the anticipated hiring base salary range for this position is$95,500.00-$138,550.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation. Moody’s also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion or creed, national origin, ancestry, citizenship, marital or familial status,sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, military or veteran status, or any other characteristic protected by law. Moody’s also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws. If you need to inquire about a reasonable accommodation, please email accommodations@moodys.com. This contact information is for accommodation requests only, and cannot be used to inquire about the status of applications

For San Francisco positions, qualified applicants with criminal histories will be considered for employment consistent with the requirements of the San Francisco Fair Chance Ordinance.

This position may be considered a promotional opportunity, pursuant to the Colorado Equal Pay for Equal Work Act.

Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.

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