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Freelance Machine Learning Data Annotation Jobs in Chicago, IL

GCP Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

Collaborate with data architects, business analysts, and machine learning teams to deliver trusted datasets. * Translate business requirements into scalable data solutions. * Provide technical ...

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

Chicago, IL An AI/ML Engineer designs, develops, and deploys production-ready artificial intelligence and machine learning models and systems, managing data pipelines, running experiments, and ...

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems ... Build predictive maintenance models using sensor data to anticipate equipment failures * Implement ...

Showing results 41-60

Freelance Machine Learning Data Annotation information

See Chicago, IL salary details

$13

$22

$36

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

As of Aug 13, 2026, the average hourly pay for freelance machine learning data annotation in Chicago, IL is $22.53, according to ZipRecruiter salary data. Most workers in this role earn between $17.84 and $25.77 per hour, depending on experience, location, and employer.

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.

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 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 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 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 Freelance Machine Learning Data Annotation jobs in Chicago, IL?

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

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

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

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

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

Staff Machine Learning Engineer

Paylocity

Schaumburg, IL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 17 days ago


Paylocity rating

7.8

Company rating: 7.8 out of 10

Based on 70 frontline employees who took The Breakroom Quiz

151st of 491 rated business services


Job description

Description:

Paylocity is an award-winning provider of cloud-based HR and payroll software solutions, offering the most complete platform for the modern workforce. The company has become one of the fastest-growing HCM software providers worldwide by offering an intuitive, easy-to-use product suite that helps businesses automate and streamline HR and payroll processes, attract and retain talent, and build a strong workplace culture.


While traditional HR and payroll providers automate basic HR processes such as payroll and benefits administration, Paylocity goes further by developing tools that HR and businesses need to compete for talent and deliver against the expectations of the modern workforce.


We give our employees what they need to succeed, including great benefits and perks! We offer medical, dental, vision, life, disability, and a 401(k) match, as well as perks that support you, your family, and your finances. And if it’s career development you desire, we provide that, too! At Paylocity, people matter most and have always been at the heart of our business.


Help Paylocity enhance communication and enable employees to connect, collaborate, and create from anywhere with a position in Product & Technology!


Want to develop the strategies and principles needed to deliver compelling software? Join our team and help us enhance our all-in-one software platform, elevate our one-of-a-kind technology, and improve the employee experience.


Take your career to the next level at one of G2's Top 100 Software Companies. Explore our Product & Technology positions to see where you fit!


This is a fully remote position, allowing you to work from home or location of record within the U.S. with no in-office requirements. You must be available five days per week during designated work hours. The work arrangement for this role is subject to change based on business needs and individual performance. This may include adjustments to on-site requirements.


Position Overview


Paylocity is growing its Machine Learning Engineering organization! 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 Staff Machine Learning Engineer in Product & Technology, you will help Paylocity build and deploy Machine Learning solutions, to help our teams build better products faster, more reliably, and at the scale we see in production for our customers. We develop machine learning models and infrastructure to support internal team strategies and collaborate closely with our data science organization to drive efficiency and best practices. Your primary focus will be to leverage your expertise in software development, machine learning algorithms, and data infrastructure to architect, develop, and optimize machine learning solutions. You will play a key role in driving the development of scalable and efficient machine learning models, contributing to the enhancement of product features, and the overall improvement of our infrastructure.


Our team is:

  • Building infrastructure that can power ML and AI features for millions of users
  • Building and deploying platform-wide recommendations to help companies follow HR best practices and allow employees to get the most out of our platform (Paylocity AI page)
  • Baking AI Ethics into all of our processes as a first-class citizen (Blog Post)
  • Working in a collaborative fully remote environment with a desire to share ideas and continuously improve
  • Invested in staying current in machine learning engineering by applying the newest tools, technologies, and practices
  • Excited to work on cutting-edge technology!


Primary Responsibilities

  • Collaborate closely with internal teams such as Data Science, Data Engineering, Paylocity’s Cloud Center of Excellence (CCOE), DevOps, and Delivery Platforms to understand requirements and ensure alignment of machine learning engineering solutions with overall business objectives and priorities.
  • 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 modeling pipelines, collaborating with internal teams to ensure smooth integration and deployment of machine learning software features.
  • Lead the optimization of CI/CD workflows, ensuring scalability and resilience while addressing complex challenges in automation in partnership with DevOps and Delivery Platforms.
  • Proactively identify and resolve issues/bugs, ensuring AppSec vulnerabilities are identified and corrected, working closely with Application Security and CCOE teams.
  • Drive the adoption of best practices in machine learning engineering across teams, contributing to the development of formal training programs and materials for MLE tool adoption.
  • Actively participate in cross-functional meetings and discussions, providing feedback, commentary, requirements, and questions to ensure alignment and drive project success.


Education and Experience


The below represents the primary duties of the position, others may be assigned as needed. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

  • Bachelor’s degree with 8 years of machine learning engineering or similar experience at software companies; or, advanced degree (master’s or PhD) in machine learning engineering, data engineering, computer science, engineering, statistics, mathematics, data science, or other quantitative field, with 3 years of demonstrated machine learning engineering success or similar experience.
  • Experience in building production-grade machine learning models and infrastructure in Python.
  • Strong background in advanced Python and big data technologies
  • Experience with cloud infrastructure (i.e., AWS, GCP, or Azure).
  • Demonstrated experience with Infrastructure as Code (IAC) tools (i.e. CDK, Pulumi, etc.).
  • Demonstrated ability to leverage machine learning engineering to drive business results.
  • Skilled at translating business problems into machine learning engineering problems and communicating the results to non-technical audiences.
  • Able to work in a collaborative environment with a desire to share your ideas.
  • Able to work independently and complete tasks with high quality, but unafraid to seek out suggestions from other team members.
  • Strong understanding of data engineering and software engineering fundamentals.
  • Self-motivated, adaptable, and highly detail oriented.


Preferred Skills

  • Professional or academic experience in HR, social science or psychology
  • Contributions to open-source software in Python
  • Enthusiastic about how machine learning and infrastructure can lead to a superior customer experience.
  • Be invested in staying current in machine learning and infrastructure by applying new technologies and practices. • Ability to sit for extended periods: The role requires sitting at a desk or workstation for long periods, typically 7-8 hours a day.
  • Use of computer and phone systems: The employee must be able to operate a computer, use phone systems, and type. This includes using multiple software programs and inquiries simultaneously.


Physical requirements

  • Ability to sit for extended periods: The role requires sitting at a desk or workstation for long periods, typically 7-8 hours a day.
  • Use of computer and phone systems: The employee must be able to operate a computer, use phone systems, and type. This includes using multiple software programs and inquiries simultaneously.

Paylocity is an equal-opportunity employer. Paylocity is committed to the full inclusion of all individuals. We recruit, train, compensate, and promote regardless of race, religion, color, national origin, sex, disability, age, veteran status, and other protected status as required by applicable law. At Paylocity, we believe diversity makes us better.
We embrace and encourage our employees’ differences in age, culture, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion or spiritual belief, sexual orientation, socio-economic status, veteran status, and other characteristics that make our employees unique. We actively cultivate these differences through our employee resource groups (ERGs), employee experiences, perspectives, talents, and approaches to drive innovation in the software and services we provide our customers.

We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. To request reasonable accommodation in the job application or interview process, please contact accessibility@paylocity.com. This email address is exclusively designated for such requests, aligning with federal and state disability laws. Please do not send resumes to this email address, as they will be removed.

The base pay range for this position is $146,600 - $209,400 /yr; however, base pay offered may vary depending on job-related knowledge, skills, and experience. This position is eligible for an annual bonus and restricted stock unit grant based on individual performance in addition to a full range of benefits outlined here . This information is provided per the relevant state and local pay transparency laws for the location in which this position will be performed. Base pay information is based on market location. Applicants should apply via www.paylocity.com/careers.

Requirements:



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