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Remote Ai Annotation Writing Jobs in Utah (NOW HIRING)

$55K - $100K/yr

Excellent written communication for high-volume outreach and candidate engagement * Scrappy, self ... annotation -- delivering the datasets that frontier AI research requires and remote workforce ...

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Remote Ai Annotation Writing information

What are some common challenges faced in remote AI annotation writing, and how can they be overcome?

Remote AI annotation writing often requires maintaining high accuracy and consistency while labeling large datasets, which can be repetitive and detail-oriented. Common challenges include understanding ambiguous content, managing distractions in a home environment, and staying updated with changing annotation guidelines. To overcome these, it's helpful to set up a dedicated workspace, communicate regularly with your team or project managers for clarification, and utilize provided training resources or feedback. Maintaining a steady workflow and taking regular breaks also helps reduce errors and burnout.

What is remote AI annotation writing?

Remote AI annotation writing involves labeling, categorizing, or adding descriptive information to data—such as text, images, audio, or video—to help train artificial intelligence and machine learning models. Workers in this role typically use specialized platforms to tag or classify data according to specific guidelines, all while working from home or another remote location. This work is essential for improving the accuracy and effectiveness of AI systems, such as those used in natural language processing or computer vision. Annotations might include identifying objects in images, transcribing audio, or highlighting sentiment in text. The job often requires attention to detail, consistency, and sometimes subject matter expertise depending on the project.

What is the difference between Remote Ai Annotation Writing vs Remote Data Labeling Specialist?

AspectRemote Ai Annotation WritingRemote Data Labeling Specialist
Primary RoleCreating and editing annotations for AI training dataLabeling and categorizing data for machine learning models
Skills RequiredAttention to detail, understanding of annotation tools, basic AI knowledgeData organization, accuracy, familiarity with labeling software
Work EnvironmentRemote, often flexible hoursRemote, often flexible hours
Industry UsageAI development, machine learning projectsAI, autonomous vehicles, healthcare, and more

Both roles involve working remotely to support AI projects, but Remote Ai Annotation Writing focuses on creating detailed annotations for training data, while Remote Data Labeling Specialist emphasizes categorizing and labeling data accurately. Understanding these differences helps job seekers find the right position aligned with their skills and career goals.

What are the key skills and qualifications needed to thrive as a Remote AI Annotation Writer, and why are they important?

To thrive as a Remote AI Annotation Writer, you need strong attention to detail, excellent written communication skills, and the ability to follow complex guidelines, typically supported by a background in linguistics, writing, or a related field. Familiarity with annotation platforms, data labeling tools, and sometimes basic knowledge of programming languages like Python can be beneficial. Adaptability, time management, and the ability to work independently are crucial soft skills for remote collaboration and meeting project deadlines. These skills ensure high-quality, accurate data annotation, which is essential for training reliable AI systems.
What are the most commonly searched types of Ai Annotation Writing jobs in Utah? The most popular types of Ai Annotation Writing jobs in Utah are:
What cities in Utah are hiring for Remote Ai Annotation Writing jobs? Cities in Utah with the most Remote Ai Annotation Writing job openings:

High Volume (TOFU) Recruiter

HumanSignal

On-site, Remote

$55K - $100K/yr

Full-time

Posted 13 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.