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Part Time Remote Data Labelling Jobs in Houston, TX

Remote We are seeking seasoned M&A 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 M&A 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 M&A 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 M&A 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 ...

Part-Time Staff Accountant

Houston, TX · Remote

$56K - $74K/yr

... and control data costs -- all without trade-offs. Our platform brings together scalable log ... Remote-friendly by design, we offer the flexibility to work where you're most effective -- whether ...

Part-Time Staff Accountant

Houston, TX · On-site +1

$52K - $69K/yr

... and control data costs - all without trade-offs. Our platform brings together scalable log ... Remote-friendly by design, we offer the flexibility to work where you're most effective - whether ...

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Part Time Remote Data Labelling information

See Houston, TX salary details

$43.9K

$157.6K

$232.5K

How much do part time remote data labelling jobs pay per year?

As of Jul 5, 2026, the average yearly pay for part time remote data labelling in Houston, TX is $157,588.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,500.00 and $162,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Part Time Remote Data Labelling specialist, and why are they important?

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 Houston, TX? The most popular types of Remote Data Labelling jobs in Houston, TX are:
What are popular job titles related to Part Time Remote Data Labelling jobs in Houston, TX? For Part Time Remote Data Labelling jobs in Houston, TX, the most frequently searched job titles are:
What job categories do people searching Part Time Remote Data Labelling jobs in Houston, TX look for? The top searched job categories for Part Time Remote Data Labelling jobs in Houston, TX are:
What cities near Houston, TX are hiring for Part Time Remote Data Labelling jobs? Cities near Houston, TX with the most Part Time Remote Data Labelling job openings:
Infographic showing various Part Time Remote Data Labelling job openings in Houston, TX as of June 2026, with employment types broken down into 100% Part Time. Highlights an 100% Remote job distribution, with an average salary of $157,588 per year, or $75.8 per hour.
Corporate Transactions Attorney - Remote

Corporate Transactions Attorney - Remote

micro1 AI

Conroe, TX • Remote

$80 - $105/hr

Part-time

Posted 11 days ago


Job description

Role Title: M&A Attorney


Role Type: Contractor


Location: Remote


We are seeking seasoned M&A attorneys for a part-time role at the forefront of legal AI. This opportunity is for elite lawyers who want to help shape how advanced AI is trained, evaluated, and applied in real-world legal work, especially those who have deep experience with drafting, reviewing, negotiating, and redlining within the tech field.


In this role, you will review, assess, and contribute to contract redlining workflows used to train and evaluate state-of-the-art AI models. Your work will directly improve how these systems identify risk and interpret contract language to create tools with improved precision and legal judgment.


Key Responsibilities:

  1. Perform simulated contract negotiations and redlining exercises.
  2. Review and assess AI responses to contract scenarios, providing expert feedback to improve model performance and output precision.
  3. Create objective evaluation frameworks and grading criteria to assess AI performance on contract tasks with rigor and consistency.
  4. Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions.


Required Skills and Qualifications:

  1. J.D. from an ABA-accredited law school.
  2. Active bar admission in at least one U.S. jurisdiction.
  3. Minimum of 2 years in the M&A department of a corporate law firm.
  4. Familiarity with standard M&A agreements, including APAs and SPAs.
  5. Exceptional written and verbal communication skills with meticulous attention to detail.
  6. Strong analytical capabilities and ability to translate legal expertise into actionable feedback for AI systems.
  7. Demonstrated commitment to innovation at the intersection of law and technology.
  8. Experience working with cross-disciplinary teams in fast-paced environments.


Preferred Qualifications:

  1. Prior exposure to AI, legal tech, or training initiatives.
  2. Experience working with private equity firms.


Why Join:

  1. This is an opportunity to work at the intersection of law and technology.
  2. You will help define how AI is developed for a new generation of legal practitioners.
  3. You will apply your experience in a high-impact research environment.