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Remote Data Labelling Jobs in Texas (NOW HIRING)

Delivery Lead

Dallas, TX ยท Remote

$110K - $140K/yr

... and remote workforce marketplaces can't. We own projects end-to-end, from scoping and protocol ... Our work spans RLHF, evals, red-teaming, and custom multimodal data creation, all powered by Label ...

We are honored to have received the "Happy at Work" and "Tech at Work" labels every year since 2019 ... If you would like more information about how your data is processed, please contact us.

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Remote Data Labelling information

See Texas salary details

$42.9K

$153.7K

$226.9K

How much do remote data labelling jobs pay per year?

As of Jul 15, 2026, the average yearly pay for remote data labelling in Texas is $153,740.00, according to ZipRecruiter salary data. Most workers in this role earn between $124,400.00 and $158,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Remote Data Labelling position, and why are they important?

To thrive as a Remote Data Labelling professional, strong attention to detail, accuracy, and basic computer literacy are essential, often requiring a high school diploma or equivalent. Familiarity with data annotation platforms, labeling tools, and sometimes experience with spreadsheet or project management software are common requirements. Excellent time management, self-motivation, and the ability to follow detailed instructions help individuals excel in this largely independent role. These qualifications are vital to ensure precise, high-quality data sets that drive effective machine learning and AI model development.

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

Remote data labelling professionals often encounter challenges such as repetitive tasks, maintaining focus over extended periods, and interpreting ambiguous data accurately. To manage these challenges, it helps to take regular breaks, use productivity techniques, and seek clarification from supervisors or team leads when instructions are unclear. Many companies provide detailed guidelines and offer online support channels to help remote labelers stay engaged and ensure consistency. Being proactive in communication and attentive to updates in instructions will contribute to both job satisfaction and data quality.

What is a Remote Data Labelling job?

A Remote Data Labelling job involves annotating, categorizing, or tagging data (such as images, text, or audio) to help train machine learning models. Workers typically use specialized tools to label data based on specific guidelines provided by companies. This role is performed entirely online, making it flexible and accessible from anywhere. It is commonly used in AI development for industries like autonomous vehicles, healthcare, and e-commerce.

What are the most commonly searched types of Data Labelling jobs in Texas? The most popular types of Data Labelling jobs in Texas are:
What are popular job titles related to Remote Data Labelling jobs in Texas? For Remote Data Labelling jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Remote Data Labelling jobs in Texas look for? The top searched job categories for Remote Data Labelling jobs in Texas are:
What cities in Texas are hiring for Remote Data Labelling jobs? Cities in Texas with the most Remote Data Labelling job openings:
Infographic showing various Remote Data Labelling job openings in Texas as of July 2026, with employment types broken down into 58% Full Time, 22% Part Time, and 20% Contract. Highlights an 100% Remote job distribution, with an average salary of $153,740 per year, or $73.9 per hour.
Delivery Lead

Delivery Lead

HumanSignal

Dallas, TX โ€ข Remote

$110K - $140K/yr

Full-time

Posted 17 days ago


Job description

About HumanSignal

Real-world data is the competitive edge in AI.

HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery.


We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide.


We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out.


If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk.

Level: Manager
Compensation: $110,000 โ€“ $140,000
Location: San Francisco, CA

About the Role

HumanSignal specializes in operationally complex, multimodal data collection and annotation โ€” delivering the datasets that frontier AI research requires and remote workforce marketplaces can't. We own projects end-to-end, from scoping and protocol design through final delivery, running on-site and distributed expert workforces across 50+ knowledge domains, 30+ languages, and 75+ countries. Our work spans RLHF, evals, red-teaming, and custom multimodal data creation, all powered by Label Studio Enterprise and built on a foundation of rigorous quality workflows, ethical sourcing, and full data security. This role sits at the operational core of that delivery engine โ€” responsible for ensuring our clients get the highest-quality data on time, every time.

This role is not for everyone. HumanSignal Services operates at the intersection of frontier AI research and large-scale human data delivery โ€” and the work is fast, demanding, and unforgiving of dropped balls. You'll own complex, high-stakes data programs end-to-end, managing expert workforces, navigating shifting customer requirements, and holding quality and delivery timelines simultaneously. There is no playbook handed to you. You will build it, break it, and rebuild it better. If you thrive under pressure, take personal pride in operational excellence, and don't quit when a project gets hard โ€” this is the role for you

What You'll Do

The day-to-day is intense by design. You'll juggle multiple programs at once, each with its own contributors, quality standards, and customer expectations. You'll make hard calls with incomplete information, hold contributors and vendors accountable, and find creative solutions to problems that don't have obvious answers. The expectation is simple: own the outcome, no excuses. High performers here grow faster than anywhere else in the industry. The bar is high โ€” and that's the point.

  • Lead and manage a team of Strategic Project Leads (SPLs) across multiple high-stakes AI data projects simultaneously
  • Own delivery outcomes for your projects: throughput, quality, SLA performance, cost efficiency, and customer satisfaction
  • Drive delivery across custom data pipelines and expert labeling workflows, translating researcher requirements into clear operational plans
  • Collaborate with AI lab researchers and procurement partners to define data strategies, scope programs, and resolve escalations
  • Drive systems-level improvements โ€” standardize playbooks, improve tooling, and build infrastructure that makes the team faster and more reliable at scale
  • Coach and develop SPLs; ensure high-quality AI Trainer experience and strong contributor retention
  • Partner with Product and Engineering to evolve internal tooling, automation, and operational systems
Required Qualifications
  • 5+ years in operationally intensive roles (marketplace, data ops, logistics, or similar)
  • 1+ year of people management with clear impact on team performance
  • Metrics-driven with a systems-thinking approach to operations
  • Experience owning delivery outcomes across multi-stakeholder, high-velocity projects
  • Hands-on operator willing to dive into execution when needed
  • Must be proficient in using LLMs in your every day work, including building scripting logic and working with large datasets with LLM assistance
Preferred Qualifications
  • 1+ year in AI data operations (RLHF, annotation, model evaluation)
  • STEM background or strong technical fluency
  • Python & REACT working knowledge
  • Experience managing distributed contributor workforces at scale
  • Background in management consulting, investment banking, or high-growth startups

HumanSignal is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. HumanSignal does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other characteristic protected by applicable federal, state, or local law. We are committed to working with and providing reasonable accommodations to individuals with disabilities.