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Remote Amazon Data Annotation Jobs in Utah (NOW HIRING)

$55K - $100K/yr

... 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 ...

... remote client service delivery. Recruiting for this role ends on 06/30/2026. Work you'll do As a ... Support data science and model teams with platform needs, environment enablement, and deployment ...

Techops Engineer -Senior Level

Farmington, UT · Remote

$99K - $136K/yr

Although position is remote employee will be required to visit data center on a quarterly basis. It ... Experience with contact center platforms (Genesys, Five9, Amazon Connect, Twilio, or similar)

Are you obsessed with data, partner success, taking action, and changing the game? If you have a ... This is a temporary, part-time contractor position that is fully remote and highly flexible.

New

Remote Amazon Data Annotation information

What is the difference between Remote Amazon Data Annotation vs Remote Mechanical Turk Worker?

AspectRemote Amazon Data AnnotationRemote Mechanical Turk Worker
CredentialsNo formal certifications required, but attention to detail helpsNo formal certifications required, basic task understanding needed
Work EnvironmentRemote, flexible hours, online platformRemote, flexible hours, online micro-task platform
Employer & IndustryAmazon, e-commerce, AI training dataVarious clients, data labeling, surveys, research

Remote Amazon Data Annotation involves labeling data specifically for Amazon's AI and e-commerce needs, often requiring attention to detail. Mechanical Turk workers perform a variety of micro-tasks across industries. While both are remote and flexible, data annotation is more specialized for AI training, whereas Mechanical Turk offers broader task types.

What are some common challenges faced by Remote Amazon Data Annotation specialists and how can they be addressed?

Remote Amazon Data Annotation specialists often encounter challenges such as maintaining consistency and accuracy across large volumes of data, managing repetitive tasks, and staying engaged while working independently. To address these, it's important to develop a strong attention to detail, utilize quality control tools provided by the platform, and take regular breaks to minimize fatigue. Additionally, staying connected with your team through regular check-ins and feedback sessions can help ensure alignment on annotation guidelines and improve overall performance.

What are Remote Amazon Data Annotation jobs?

Remote Amazon Data Annotation jobs involve labeling, categorizing, or tagging data such as images, text, or audio to help train machine learning models used by Amazon. Employees work from home using specialized tools to ensure accuracy and consistency in the data provided. These roles often require attention to detail, the ability to follow guidelines, and sometimes specific domain knowledge depending on the project. Data annotation is essential for improving the performance of AI systems in tasks like product recommendations, voice recognition, and search algorithms. These roles may be full-time, part-time, or project-based, offering flexibility for remote workers.

What are the key skills and qualifications needed to thrive as a Remote Amazon Data Annotation Specialist, and why are they important?

To thrive as a Remote Amazon Data Annotation Specialist, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a high school diploma or relevant experience. Competence with web-based annotation tools, cloud-based platforms, and sometimes Amazon-specific data systems is typically required. Diligence, consistency, effective communication, and the ability to work independently are valuable soft skills in this role. These skills and qualities are important to ensure high-quality, accurate data labeling that supports effective machine learning and AI model development.
What are the most commonly searched types of Amazon Data Annotation jobs in Utah? The most popular types of Amazon Data Annotation jobs in Utah are:
What are popular job titles related to Remote Amazon Data Annotation jobs in Utah? For Remote Amazon Data Annotation jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Remote Amazon Data Annotation jobs? Cities in Utah with the most Remote Amazon Data Annotation job openings:

High Volume (TOFU) Recruiter

HumanSignal

On-site, Remote

$55K - $100K/yr

Full-time

Posted 29 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.