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Annotation Labelling Jobs in Dallas, TX (NOW HIRING)

HumanSignal

Delivery Lead

Dallas, TX · Remote

$110K - $140K/yr

... 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 ...

HumanSignal

High Volume (TOFU) Recruiter

Dallas, TX · On-site +1

$55K - $100K/yr

... 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 ...

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RWS TrainAI

Language Data Annotator (US)

Dallas, TX · On-site +1

Experience in one or more of the following areas: machine learning tasks, data collection and preprocessing, data evaluation and quality assurance, and data annotation and labeling. What We Offer

RWS TrainAI

Language Data Annotator (US)

Dallas, TX · On-site +1

Experience in one or more of the following areas: machine learning tasks, data collection and preprocessing, data evaluation and quality assurance, and data annotation and labeling. What We Offer

Sradha Technologies LLC

Senior ML Engineer

Dallas, TX · On-site +1

$103.80K - $142.60K/yr

Define and build the training data model and annotation schema for structured outputs (intent ... datasets, labeling frameworks, and structured output schemas for multi-task NLP systems. Strong ...

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Annotation Labelling information

What are the key skills and qualifications needed to thrive as an Annotation Labelling Specialist, and why are they important?

To thrive as an Annotation Labelling Specialist, you need strong attention to detail, data analysis capabilities, and familiarity with data annotation standards, usually supported by a background in computer science or related fields. Proficiency with annotation tools such as Labelbox, CVAT, or Supervisely, and sometimes knowledge of basic programming or scripting, is typically required. Excellent communication, consistency, and the ability to follow complex instructions are crucial soft skills for producing high-quality labeled data. These skills ensure the accuracy and reliability of datasets, which are foundational for successful machine learning and AI model development.

What are some common challenges faced by Annotation Labelling professionals, and how can they be managed?

Annotation Labelling professionals often encounter challenges such as maintaining high accuracy while handling repetitive data, meeting tight deadlines, and adapting to evolving project guidelines. To manage these, it’s important to develop strong attention to detail, regularly communicate with team leads to clarify instructions, and leverage annotation tools efficiently. Collaborating closely with quality assurance teams can also help identify and correct errors early, ensuring consistently high-quality outputs.

What is annotation labelling?

Annotation labelling is the process of tagging or marking data—such as images, text, or audio—with relevant information or labels. This is an essential step in preparing datasets for machine learning and artificial intelligence models, as it helps algorithms understand and learn from raw data. Annotation labelling can include tasks like identifying objects in photos, transcribing speech, or categorizing text. Skilled annotators ensure accuracy and consistency to improve model performance. People in this role often use specialized tools or software to streamline and standardize the annotation process.

What is the difference between Annotation Labelling vs Data Labeling Specialist?

AspectAnnotation LabellingData Labeling Specialist
CredentialsBasic technical skills, attention to detailSimilar skills, sometimes additional domain knowledge
Work EnvironmentData annotation platforms, remote or officeData annotation tasks, often remote or in-office
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, healthcare, retail
Search & ComparisonCommonly compared for entry-level data tasksRelated but broader role

Annotation Labelling involves marking data such as images, text, or videos to train AI models. Data Labeling Specialists perform similar tasks but may have a broader scope, including verifying and managing labeled data. Both roles are essential in AI development, often overlapping in skills and work environment, but Annotation Labelling is more focused on the annotation process itself.

What are popular job titles related to Annotation Labelling jobs in Dallas, TX? For Annotation Labelling jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Annotation Labelling jobs in Dallas, TX look for? The top searched job categories for Annotation Labelling jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Annotation Labelling jobs? Cities near Dallas, TX with the most Annotation Labelling job openings:
Annotation Labelling jobs near you

Delivery Lead

HumanSignal

Dallas, TX • Remote

$110K - $140K/yr

Full-time

Posted 3 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 – $140,000
Location: San Francisco, CA

About the Role

HumanSignal specializes in operationally complex, multimodal data collection and annotation — 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 — 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 — 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 — 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 — 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 — 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.