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Part Time Remote Data Labelling Jobs in Illinois

Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Software ... Interpret and annotate technical data to support AI model training and evaluation. * Collaborate ...

Posted today

Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Finance Domain ... Assess and annotate financial data, reports, and AI-generated outputs using structured evaluation ...

Posted today

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Showing results 21-40

Part Time Remote Data Labelling information

What are the key skills and qualifications needed to thrive as a part time remote data labelling specialist?

To excel as a Part Time Remote Data Labelling specialist, you need strong attention to detail, basic computer literacy, and a solid understanding of data privacy and handling protocols, often requiring a high school diploma or equivalent. Familiarity with annotation platforms, spreadsheet software, and sometimes specific data labelling tools like Labelbox or Supervisely is typically required. Reliability, time management, and clear communication are crucial soft skills for meeting deadlines and collaborating in a remote setting. These skills and qualities ensure that labelled data is accurate, consistent, and valuable for training effective machine learning models.

What is the difference between Part Time Remote Data Labelling vs Part Time Remote Data Annotation?

AspectPart Time Remote Data LabellingPart Time Remote Data Annotation
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, data processingAI, machine learning, data processing
Job FocusLabeling data for training AI modelsAnnotating data for AI training

Part Time Remote Data Labelling and Part Time Remote Data Annotation are similar roles involving preparing data for AI systems. Labelling typically involves categorizing data, while annotation may include adding detailed notes or markings. Both roles require attention to detail and are performed remotely, making them suitable for flexible schedules. The main difference lies in the specific tasks, but they are often used interchangeably depending on the employer or project.

What is a part time remote data labelling job?

A part time remote data labelling job involves annotating or tagging data—such as images, text, or audio—from your own location, typically using specialized software provided by employers. The role is essential for training machine learning models, as accurate labels help computers learn to recognize patterns. These jobs are often flexible, allowing you to set your own hours and work from anywhere with an internet connection. No advanced technical skills are usually required, but attention to detail is important.

What are some common challenges faced by part time remote data labelling professionals, and how can they be managed?

Part-time remote data labellers often face challenges such as maintaining consistent accuracy, staying focused during repetitive tasks, and managing communication with a distributed team. To address these, it’s helpful to establish a quiet, distraction-free workspace, use productivity techniques like the Pomodoro method, and regularly review labelling guidelines to minimize errors. Leveraging communication tools and participating in team check-ins can also help clarify questions and build a sense of connection with colleagues.
What are the most commonly searched types of Remote Data Labelling jobs in Illinois? The most popular types of Remote Data Labelling jobs in Illinois are:
What job categories do people searching Part Time Remote Data Labelling jobs in Illinois look for? The top searched job categories for Part Time Remote Data Labelling jobs in Illinois are:
What cities in Illinois are hiring for Part Time Remote Data Labelling jobs? Cities in Illinois with the most Part Time Remote Data Labelling job openings:
Infographic showing various Part Time Remote Data Labelling job openings in Illinois as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

AI Software Engineer Expert - Remote

YO AI Labs

Chicago, IL • Remote

$100 - $200/hr

Part-time

Posted 18 hours ago

Posted today


Job description

Job Title: AI Software Engineering Domain Remote

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Software Engineering Domain Experts to contribute their technical expertise to an innovative project focused on improving next-generation AI systems. In this role, you will evaluate, review, and refine AI-generated software engineering content to enhance the quality, accuracy, and reasoning of AI models. No prior AI experience is required—your software engineering expertise is what matters most.

Key Responsibilities
  • Analyze, review, and improve AI-generated software engineering content for technical accuracy and clarity.
  • Create, refine, and evaluate prompts to improve AI-generated technical outputs.
  • Conduct rubric-based evaluations of AI model responses, providing detailed quality feedback.
  • Draft and edit technical documentation, architecture documents, RFCs, design specifications, and engineering proposals.
  • Perform independent research and fact-checking to validate technical information.
  • Interpret and annotate technical data to support AI model training and evaluation.
  • Collaborate remotely with cross-functional teams to deliver high-quality project outcomes.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Quality Assurance
  • Prompt Engineering
  • AI Output Evaluation
  • Technical Documentation
  • Technical & Professional Writing
  • Content Review & Editing
  • Data Annotation
  • Fact Checking
  • Independent Research
  • Business Communication
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of professional experience as a Software Engineer, Senior Software Engineer, Staff Engineer, Technical Lead, Engineering Manager, Solutions Architect, or similar role.
  • Experience authoring or reviewing technical documentation, architecture documents, RFCs, design specifications, engineering proposals, postmortems, technical blogs, or code reviews.
  • Strong critical thinking, analytical reasoning, and structured problem-solving skills.
  • Excellent written communication and technical editing abilities.
  • Experience with AI coding tools or automated documentation tools is a plus but not required.
  • Advanced degree (Master's, MBA, JD, or PhD) or equivalent professional experience is preferred.