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Internship Ai Data Annotation Jobs in Michigan (NOW HIRING)

Saransh Inc

Senior Robotics Data Engineer - Only W2

Warren, MI · On-site

$99K - $135K/yr

... AI. · Familiarity with robotics simulation platforms (e.g., Isaac Sim) and synthetic data generation. · Experience with data labeling tools and annotation workflows at scale. · Hands-on knowledge ...

Autoliv United States

GenAI Intern

Auburn Hills, MI

$14.25 - $19/hr

Currently pursuing a degree in CS, AI, Data Science, or related field * Availability to work on site 4 days a week, part time * Availability to complete a 1 year internship * Basic Python or ...

Autoliv United States

GenAI Intern

Auburn Hills, MI · On-site

$14.25 - $19/hr

Currently pursuing a degree in CS, AI, Data Science, or related field * Availability to work on site 4 days a week, part time * Availability to complete a 1 year internship * Basic Python or ...

Magna

Supply Chain Internship

Highland Park, MI · On-site

$16.25 - $22/hr

The internship program is a continuous program offering 30 hours per week; flexible based on class ... Importantly, no applicant data is shared externally through these AI tools. All information remains ...

Magna

Supply Chain Internship

Highland Park, MI

$16.25 - $22/hr

The internship program is a continuous program offering 30 hours per week; flexible based on class ... Importantly, no applicant data is shared externally through these AI tools. All information remains ...

Kla

AI Systems and Operations Specialist

Ann Arbor, MI

$87K - $148K/yr

Our expert teams of physicists, engineers, data scientists and problem-solvers work together with ... Interns are eligible for some of the benefits listed. Our pay ranges are determined by role, level ...

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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 Internship AI Data Annotation specialist, and why are they important?

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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Internship Ai Data Annotation jobs near you

English (US) Audio QA Annotation Specialist

MatchaTalent

Ann Arbor, MI • On-site, Remote

Full-time

Posted 15 days ago

Job description

This role requires the candidate to work remotely from the United States.


Client Overview

Our client is a global artificial intelligence technology company specializing in the development of advanced large language models (LLMs), speech recognition technologies, multilingual AI systems, and data annotation solutions. The organization collaborates with leading AI research laboratories and enterprise technology companies worldwide to accelerate the development of next-generation artificial intelligence through high-quality human-generated data.

Supporting a diverse portfolio of multilingual AI initiatives, the company works with language specialists, voice professionals, and annotation experts across the globe to improve the accuracy, contextual understanding, and performance of cutting-edge AI systems used in speech processing, conversational AI, and natural language understanding.


Job Role

The English (US) Audio QA Annotation Specialist is responsible for reviewing, evaluating, and validating English (US) audio recordings to ensure they meet the highest quality standards required for AI speech recognition and audio annotation projects.

Working as part of a multilingual quality assurance team, this role focuses on assessing recording accuracy, pronunciation, fluency, audio clarity, annotation consistency, and compliance with project guidelines. The successful candidate will help ensure that all approved audio data contributes effectively to the development of advanced multilingual AI speech technologies.


Key Responsibilities

  • Review and evaluate English (US) audio recordings for quality, pronunciation accuracy, clarity, and natural speech delivery.
  • Verify annotation accuracy and ensure all submitted recordings comply with project guidelines and quality standards.
  • Identify audio quality issues including background noise, recording inconsistencies, pronunciation errors, or technical defects.
  • Provide structured quality feedback and recommend improvements when recordings do not meet required standards.
  • Ensure consistency across annotated datasets by following established QA processes and evaluation criteria.
  • Collaborate with project reviewers and annotation teams to maintain high-quality multilingual datasets.
  • Maintain accurate documentation of review outcomes and quality assurance findings.
  • Support the continuous improvement of AI speech recognition models through high-quality audio validation.


Candidate Requirements

  • Native-level fluency in English (US) with excellent listening comprehension and pronunciation knowledge.
  • Minimum 1 year of experience in audio quality assurance, audio annotation, localization, transcription review, voice-over, dubbing, ADR, or related language quality roles.
  • Strong attention to detail with the ability to identify pronunciation, fluency, and audio quality issues accurately.
  • Excellent understanding of American English linguistic nuances, regional accents, grammar, and natural speech patterns.
  • Experience reviewing audio recordings and applying quality standards consistently.
  • Familiarity with audio editing or audio playback software is preferred.
  • Strong analytical skills with the ability to provide clear and actionable quality feedback.
  • Ability to work independently while meeting project deadlines and quality targets.


Job Code: #784