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Internship Ai Data Annotation Jobs in Ohio (NOW HIRING)

High Volume (TOFU) Recruiter

Columbus, OH · On-site +1

$55K - $100K/yr

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 ...

$18 - $23.50/hr

ABOUT PERLE Perle is an AI infrastructure company building expert-driven training data, evaluation ... Comfortable with web-based annotation platforms and variable-speed audio playback * Reliable high ...

$109K - $131K/yr

... or internship experience in machine learning, AI, or data-driven projects. • Solid understanding of algorithms, data structures, and machine learning concepts. • Experience with data ...

Agentic AI Engineer

Cincinnati, OH · On-site

$105K - $127K/yr

... or internship experience in machine learning, AI, or data-driven projects. • Solid understanding of algorithms, data structures, and machine learning concepts. • Experience with data ...

Process Improvement & AI Intern

Canton, OH · On-site

$19.25 - $33.50/hr

... Internship Assignment: Full Time - Summer 2027 * Start date: 05/17/2027 * Assist with AI and advanced analytics projects, including data preparation, analysis, and visualization. * Support continuous ...

... Internship Assignment: Full Time - Summer 2027 * Start date: 05/17/2027 * Assist with AI and advanced analytics projects, including data preparation, analysis, and visualization. * Support continuous ...

Showing results 21-40

Internship Ai Data Annotation information

What are the typical challenges faced during an AI data annotation internship, and how can I overcome them?

As an AI Data Annotation intern, you may encounter challenges such as maintaining high accuracy while labeling large volumes of data, understanding complex annotation guidelines, and adapting to evolving project requirements. It's important to regularly communicate with your team lead or project manager to clarify any uncertainties and ensure consistency in your annotations. Leveraging available training materials and asking for feedback will help you improve your efficiency and accuracy, turning these challenges into valuable learning experiences.

What is an AI data annotation internship?

An AI Data Annotation Internship is a temporary position where interns help label, tag, or categorize data (such as images, text, or audio) to train and improve artificial intelligence models. Interns typically work with datasets, ensuring that the information provided is accurate and consistent, which is crucial for machine learning algorithms to learn effectively. The role is a valuable entry point for those interested in AI, machine learning, or data science, as it offers hands-on experience with the foundational work needed to build intelligent systems.

What is the difference between Internship Ai Data Annotation vs Data Labeler?

AspectInternship Ai Data AnnotationData Labeler
CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; minimal formal education required
Work EnvironmentOffice or remote; supervised tasks, often part-time or temporaryOffice or remote; repetitive tasks, often entry-level
Industry UsageTech companies, AI startups, research projectsTech firms, data companies, AI development teams
Search & Comparison IntentUnderstanding entry-level roles in AI data annotationComparing entry-level data labeling jobs in AI

Internship Ai Data Annotation roles typically involve supervised, short-term tasks aimed at gaining experience in AI data preparation. Data Labeler positions are similar entry-level roles focused on labeling data for machine learning. Both roles require basic skills and are used across tech and AI industries, but internships often offer more training and learning opportunities.

What are the key skills and qualifications needed to thrive as an AI data annotation intern?

To thrive as an Internship AI Data Annotation specialist, you need attention to detail, basic computer literacy, and a foundational understanding of data labeling concepts, often supported by ongoing training or coursework in data science or computer science. Familiarity with annotation tools like Labelbox, Supervisely, or VIA, and knowledge of data management platforms are commonly required. Strong organizational skills, patience, and effective communication help you manage repetitive tasks and collaborate with team members. These skills are essential to ensure high-quality data labeling, which directly impacts the performance and accuracy of AI models.
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What cities in Ohio are hiring for Internship Ai Data Annotation jobs? Cities in Ohio with the most Internship Ai Data Annotation job openings:

High Volume (TOFU) Recruiter

HumanSignal

Columbus, OH • On-site, Remote

$55K - $100K/yr

Full-time

Re-posted 14 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.