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Freelance Machine Learning Data Annotation Jobs in McHenry, IL

Varsity Tutors

Machine Learning Tutor

Schaumburg, 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 ...

Varsity Tutors

Machine Learning Tutor

Buffalo Grove, 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 ...

Varsity Tutors

Machine Learning Tutor

Lake Forest, 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 ...

Paylocity

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 ...

Varsity Tutors

Data Science Tutor

Buffalo Grove, IL · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Varsity Tutors

Data Science Tutor

Lake Forest, IL · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Varsity Tutors

Data Science Tutor

Schaumburg, IL · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Motorola

Senior Data Scientist (Hybrid)

Schaumburg, IL · Hybrid

$120K - $140K/yr

Machine Learning & Statistical Modeling to design predictive infrastructure and deploy statistical algorithms * Data Mining & Analytics to process large-scale datasets and extract operational ...

Grainger Businesses

Data Engineer III

Lake Forest, IL · Hybrid

$104K - $174K/yr

This role reports to a Senior Manager of Machine Learning Engineering and partners closely with ... This role will own the data foundation behind ML and analytics use cases, enabling faster decision ...

Grainger Businesses

Data Engineer III

Lake Forest, IL · On-site

$104K - $174K/yr

This role reports to a Senior Manager of Machine Learning Engineering and partners closely with ... This role will own the data foundation behind ML and analytics use cases, enabling faster decision ...

Grainger Businesses

Data Engineer III

Lake Forest, IL · Hybrid

$104K - $174K/yr

This role reports to a Senior Manager of Machine Learning Engineering and partners closely with ... This role will own the data foundation behind ML and analytics use cases, enabling faster decision ...

AbbVie

Principal Data Scientist

Mettawa, IL · On-site

The position requires deep expertise in applied machine learning, statistical modeling ... The Principal Data Scientist may lead technical workstreams with external analytics vendors and ...

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All JobsMachine Learning Data Annotation JobsFreelance Machine Learning Data Annotation JobsFreelance Machine Learning Data Annotation Jobs in McHenry, IL

Freelance Machine Learning Data Annotation information

See McHenry, IL salary details

$12

$21

$34

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

As of Sep 3, 2026, the average hourly pay for freelance machine learning data annotation in McHenry, IL is $21.52, according to ZipRecruiter salary data. Most workers in this role earn between $17.02 and $24.62 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 job categories do people searching Freelance Machine Learning Data Annotation jobs in McHenry, IL look for?

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

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

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

Freelance Machine Learning Data Annotation jobs near you
Infographic showing various Freelance Machine Learning Data Annotation job openings in McHenry, IL as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, 3% Contract, and 1% Nights. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $44,771 per year, or $21.5 per hour.

Machine Learning PhD Student Contributor

Cobalt

Mundelein, IL • On-site

Other

Posted 4 days ago

Key responsibilities

  • Produce written reasoning traces on complex ML problems and draft expert reference answers to technical questions

  • Evaluate model-generated technical content by comparing responses, articulating strengths, and identifying points of failure in reasoning

  • Assess whether conclusions are supported by derivations, code, or experimental evidence and contribute to project guidelines and dataset development

Job description

About the role:

Cobalt is seeking PhD-qualified machine learning researchers with direct experience designing, running, and evaluating original ML research. This opportunity is suited to researchers who have worked in academic ML labs, industry research groups, or frontier lab environments, and who understand how technical claims are established, tested, and supported by evidence.

You may currently work, or have previously worked, as a PhD candidate, Postdoctoral Researcher, Research Scientist, Research Engineer, Applied Scientist, Member of Technical Staff, or in a related role.

You do not need prior experience in data annotation or model evaluation. You must, however, have contributed meaningfully to at least one substantive ML research output, and you must be comfortable reading papers, interpreting experimental results, and judging whether stated conclusions follow from the underlying evidence.


What you'll do:

Depending on the project, you may:

  • Produce written reasoning traces on hard ML problems, capturing how you reach a solution rather than only the solution itself, and draft expert reference answers to technical questions
  • Author novel problems in your subfield that have verifiable or defensible correct answers
  • Evaluate model-generated technical content: compare and rank responses, articulate what makes the stronger one stronger, and identify the specific step at which a chain of reasoning breaks down
  • Assess whether stated conclusions are supported by the underlying derivation, code, or experimental evidence
  • Design rubrics and partial-credit criteria for scoring multistep technical tasks, and contribute subject-matter expertise to benchmark and dataset development

Projects follow their own annotation guidelines and quality standards, and you will work with feedback from reviewers and lab research teams.


Required qualifications:

  • PhD, completed or in progress, in machine learning, computer science, statistics, mathematics, physics, or a closely related quantitative discipline, with research that is substantially ML focused
  • Direct experience authoring, co-authoring, or substantively contributing to at least one ML research output, such as a peer-reviewed paper, preprint, thesis chapter, or comparable technical artifact
  • Demonstrated depth in at least one area, for example optimization, reinforcement learning, language model training and post-training, learning theory, probabilistic methods, computer vision, natural language processing, or systems for ML
  • Ability to interpret papers, derivations, code and experimental results, and to explain your reasoning clearly in writing
  • Strong attention to detail, a commitment to factual accuracy, and the ability to work independently to agreed timelines


Why join Cobalt AI:

  • Advance frontier AI where it counts. Apply your research expertise to the data that frontier labs cannot obtain any other way, where your reasoning directly shapes how the next generation of models works through technical problems.
  • Grow professionally. Expand your influence through evaluation projects, advisory roles, and research collaborations, while deepening your understanding of how frontier models are trained and assessed.
  • Work with a top-tier network. Collaborate with researchers from leading institutions and labs on high-impact, flexible work.
  • Set your own schedule. Flexible 10 to 40 hour weeks that fit around your research position and your life.
  • Competitive pay. Rates vary by project and are determined by a number of factors, including scope, skillset, and experience.

Apply