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Data Labeler Remote Jobs in Utah (NOW HIRING)

$55K - $100K/yr

... standard for data labeling and evaluation, used by over 1 million practitioners worldwide. We ... San Francisco, CA preferred; open to other remote options About the Role HumanSignal Services runs ...

The NQ Plan Analyst team (Direct and Private Label) oversees the day-to-day workflow for assigned ... Research data issues, including information on Risk Mitigation reports, to ensure data completeness.

$41.20 - $62.17/hr

Data Analysis & Compliance: Tracks key metrics, analyze trends, and ensure regulatory compliance ... Ongoing need for employee to see and read information, labels, documents, monitors, identify ...

New

Account Manager

Salt Lake City, UT · Remote

$90K - $100K/yr

... label systems. Markem-Imaje delivers fully integrated solutions that enable product quality and ... Remote Pay Range: $90,000.00 - $100,000.00 annually Commission Eligible: This position is eligible ...

Account Manager

Salt Lake City, UT · Remote

$90K - $100K/yr

... label systems. Markem-Imaje delivers fully integrated solutions that enable product quality and ... Ability to identify problems, collect data, establish facts, and draw valid conclusions. Successful ...

Account Manager

Salt Lake City, UT · Remote

$90K - $100K/yr

... label systems. Markem-Imaje delivers fully integrated solutions that enable product quality and ... Remote Pay Range: $90,000.00 - $100,000.00 annually Commission Eligible: This position is eligible ...

Data Labeler Remote information

Is data labeling a good career?

Data labeling is a common entry-level role in the AI and machine learning industry, involving annotating data such as images, text, or audio to train algorithms. It often offers flexible remote work options and requires attention to detail and basic technical skills. While it can provide a stepping stone into tech-related fields, it may have limited advancement opportunities without additional skills or certifications.

What are the key skills and qualifications needed to thrive as a remote data labeler?

To thrive as a Data Labeler Remote, you need strong attention to detail, basic data analysis skills, and familiarity with data annotation processes, often supported by a high school diploma or equivalent. Proficiency with labeling platforms, annotation tools, and sometimes knowledge of spreadsheet software are typically required. Reliability, time management, and effective communication are crucial soft skills for maintaining accuracy and meeting project deadlines in a remote setting. These skills ensure high-quality, consistent labeled data, which is essential for training reliable machine learning models.

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

Remote data labelers often encounter challenges such as maintaining focus during repetitive tasks, ensuring consistent annotation quality, and communicating effectively with distributed teams. To manage these, it's helpful to establish a structured work routine, take regular breaks to prevent fatigue, and use annotation guidelines provided by employers. Leveraging collaboration tools for feedback and clarification also helps maintain high-quality output and fosters a sense of connection with team members.

How much do data labelers get paid?

Data labelers working remotely typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the company. Some roles may offer project-based pay or bonuses, and familiarity with labeling tools can improve earning potential.

What does a remote data labeler do?

A remote data labeler is responsible for annotating or tagging data—such as images, videos, audio, or text—from a remote location, typically working from home. Their work helps train machine learning models by providing accurate, labeled datasets that algorithms use to learn and make predictions. Data labelers follow specific guidelines to ensure consistency and accuracy, and may use specialized software tools to complete their tasks. This role is essential in industries like artificial intelligence, self-driving cars, and natural language processing. Remote data labelers often work as freelancers or as part of distributed teams for tech companies.

What is the difference between Data Labeler Remote vs Data Annotator Remote?

AspectData Labeler RemoteData Annotator Remote
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageCommon in AI/ML data preparationCommon in AI/ML data preparation
Job FocusLabeling data points for machine learningAnnotating data for training AI models

Both Data Labeler Remote and Data Annotator Remote roles involve preparing data for AI and machine learning projects. While the terms are often used interchangeably, Data Labeler Remote typically emphasizes labeling data points, whereas Data Annotator Remote may include more detailed annotation tasks. Both roles require similar skills and are performed remotely, making them accessible for individuals seeking flexible data-related jobs.

What are the most commonly searched types of Data Labeler jobs in Utah? The most popular types of Data Labeler jobs in Utah are:
What are popular job titles related to Data Labeler Remote jobs in Utah? For Data Labeler Remote jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Data Labeler Remote jobs? Cities in Utah with the most Data Labeler Remote job openings:
Infographic showing various Data Labeler Remote job openings in Utah as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

High Volume (TOFU) Recruiter

HumanSignal

On-site, Remote

$55K - $100K/yr

Full-time

Re-posted 10 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: Individual Contributor 
Compensation: $55,000 – $100,000
Location: San Francisco, CA preferred; open to other remote options

About the Role

HumanSignal Services runs on expert talent — and we need a lot of it, fast. As our high-volume recruiter, you are the engine that keeps our data programs fully staffed with the right contributors at the right time. This isn\'t a post-and-pray recruiting role. You\'ll be proactive, scrappy, and relentless — sourcing, screening, and moving candidates through a pipeline that never stops. When a program needs 500 vetted domain experts in 72 hours, you\'re the one who makes it happen. Speed matters here, but so does quality — the wrong contributor wastes everyone\'s time and hurts the data. You\'ll own both.

What You\'ll Do

You\'ll run high-volume sourcing across multiple channels simultaneously — job boards, LinkedIn, niche communities, referral networks, and anywhere else qualified talent lives. You\'ll screen candidates quickly and accurately, matching domain expertise to program requirements. You\'ll own pipeline health metrics — application volume, time-to-fill, screen-to-hire ratios — and hold yourself accountable to them daily. You\'ll work hand-in-hand with Strategic Project Leads and Operations to understand what each program actually needs, not just what the job description says. When a pipeline dries up or a new program spins up overnight, you don\'t wait to be told — you move. The programs don\'t stop for recruiting, so recruiting can\'t stop either.

  • Source and screen high volumes of candidates across multiple active programs simultaneously, maintaining quality and speed without sacrificing either
  • Own top-of-funnel pipeline health: track application volume, conversion rates, time-to-fill, and screen-to-hire ratios daily
  • Partner closely with Strategic Project Leads and Operations to understand program-specific requirements — domain expertise, availability windows, technical qualifications, and quality standards
  • Build and maintain sourcing pipelines across job boards, LinkedIn, academic networks, professional communities, and referral programs
  • Develop and iterate on outreach messaging, job descriptions, and screening criteria to improve conversion at every stage of the funnel
  • Coordinate scheduling and logistics for screening calls, assessments, and onboarding hand-offs
  • Flag pipeline risks early — if a program is at risk of understaffing, surface it before it becomes a delivery problem
  • Continuously improve sourcing strategies based on data; identify which channels produce the best contributors for each domain
Required Qualifications
  • 2+ years of high-volume recruiting or sourcing experience
  • Proven track record managing large candidate pipelines under tight timelines
  • Strong organizational skills; comfortable juggling multiple open requisitions at once
  • Data-driven: comfortable tracking and reporting on funnel metrics
  • Excellent written communication for high-volume outreach and candidate engagement
  • Scrappy, self-directed, and comfortable operating with minimal process in a fast-moving environment
Preferred Qualifications
  • Experience recruiting for technical, domain-expert, or gig/contractor workforces
  • Familiarity with AI data operations, annotation, or RLHF workforce programs
  • Experience with ATS platforms (Greenhouse, Ashby, Lever, or similar)
  • Background in marketplace operations, staffing, or workforce platforms
About HumanSignal

HumanSignal Services 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.

Equal Opportunity Employer

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.