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Internship Ai Annotation Jobs (NOW HIRING)

FieldAI

Senior Data Operations Engineer

Boston, MA

$110K - $140K/yr

... interns and contractors who carry out the bulk of day-to-day collection and annotation. You'll work ... Why Join Field AI? FieldAI is tackling one of robotics' hardest problems: deploying robots in ...

FieldAI

Senior Data Operations Engineer

Boston, MA

$110K - $140K/yr

About the Role Field AI is transforming how robots interact with the real world. Our R&D team, the ... interns and contractors who carry out the bulk of day-to-day collection and annotation. You'll work ...

FieldAI

Senior Data Operations Engineer

Boston, MA · On-site

$110K - $140K/yr

About the Role Field AI is transforming how robots interact with the real world. Our R&D team, the ... interns and contractors who carry out the bulk of day-to-day collection and annotation. You'll work ...

Helm.ai

Senior Software Engineer

$150K - $250K/yr

Helm.ai builds AI software for autonomous driving and robotics. Our Deep Teaching™ methodology is ... Our unsupervised learning software can train neural networks without the need for human annotation ...

The Pennsylvania State University

This fall/spring internship willconcentrate on gaining hands-on experience in AI/ML data ... Previous experience with data analysis or annotation at any level You will work up to 20 hours/week ...

Aicadium

Sr. Research Data Scientist

San Diego, CA

Own the full data lifecycle for visual tasks: dataset curation, annotation strategy, augmentation ... internships, or substantial project experience in computer vision, robotics, or embodied AI.

AIcadium

Sr. Research Data Scientist

San Diego, CA · On-site

$150K - $180K/yr

Own the full data lifecycle for visual tasks: dataset curation, annotation strategy, augmentation ... internships, or substantial project experience in computer vision, robotics, or embodied AI.

Labelbox

Cyber Security Intern

San Francisco, CA · On-site

... frontier AI development: * Enterprise Platform & Tools : Advanced annotation tools, workflow ... This is an hourly internship position. Your Impact * Support day to day triage and analysis of ...

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Internship Ai Annotation information

What are the typical responsibilities of an AI Annotation Intern, and how do they contribute to the overall AI development process?

As an AI Annotation Intern, your primary responsibility is to label and categorize large sets of data—such as images, text, or audio—which are crucial for training and improving machine learning models. You'll work closely with data scientists, machine learning engineers, and other annotators to ensure accuracy and consistency in the datasets. This role often involves using specialized annotation tools, reviewing outputs, and flagging ambiguous data. Your work is vital for building high-quality AI systems, and you'll gain valuable insights into how annotated data directly impacts model performance and decision-making. Additionally, interns often have opportunities to learn about the end-to-end AI development process and may progress into more advanced roles with experience.

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

AspectInternship Ai AnnotationData Labeler
CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; minimal technical requirements
Work EnvironmentOffice or remote; collaborative with AI/tech teamsOffice or remote; focused on data preparation tasks
Industry UsageAI development, machine learning projectsData management, AI training datasets
Search & Comparison IntentUnderstanding roles in AI data annotationSimilar data labeling roles in AI projects

Internship Ai Annotation typically involves entry-level tasks in AI data annotation, often as part of an internship program, focusing on labeling data for machine learning models. Data Labelers perform similar tasks but may not be part of an internship and often work on larger datasets. Both roles require basic technical skills and are essential in AI development, but internships usually offer training and career development opportunities.

What are the key skills and qualifications needed to thrive as an AI Annotation Intern, and why are they important?

To thrive as an AI Annotation Intern, you need attention to detail, basic data analysis skills, and familiarity with data labeling concepts, usually supported by coursework in computer science or related fields. Experience with annotation tools like Labelbox, Supervisely, or CVAT, as well as understanding of data privacy protocols, is highly valuable. Strong communication, time management, and the ability to follow complex guidelines help you excel in this position. Mastering these skills ensures high-quality, accurate datasets that are critical for training reliable AI models.

What is an AI Annotation Intern?

An AI Annotation Intern is someone who helps train artificial intelligence models by labeling and categorizing data, such as images, text, or audio. This process, known as data annotation, is crucial for improving the accuracy of machine learning algorithms. Interns typically work under supervision to ensure the data is correctly tagged according to specific guidelines. The role provides hands-on experience in the field of AI and machine learning, often requiring attention to detail and familiarity with annotation tools.
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Infographic showing various Internship Ai Annotation job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Senior Data Management Professional - Data Engineering (Data AI)

Bloomberg LP

Princeton, NJ • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 17 days ago

Bloomberg rating

9.4

Company rating: 9.4 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

12th of 241 rated software companies

Job description

Senior Data Management Professional - Data Engineering (Data AI)
Location
Princeton
Business Area
Data
Ref #
10052626
Description & Requirements
Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.
Our Team:
Data AI contributes to the building of Bloomberg's AI-enhanced products at scale by curating model training data and enhancing how our internal processes use AI. We provide evaluation and annotation frameworks connecting natural language processing and human judgment in order to elevate the quality, intelligence, and usability of the data that drives our products.
By investing in AI at a strategic level, we expand our practice of engaging with AI to one that is embedded across Data. Our internal processes to take advantage of new AI technologies and strengthen Data's role in providing robust domain expertise and influential data artifacts to Bloomberg's products. As a result our clients will continue to have high quality data and access to new types of datasets.
The Role:
As a Data Engineer within Data AI, you will build and evolve the infrastructure, data pipelines, and operational tooling that power scalable AI and data workflows. You will enable reliable data collection, annotation, training, and evaluation processes by developing systems that improve data quality, operational visibility, and workflow efficiency. Through automation, observability, and platform engineering, you will help create the foundations that allow teams to deliver data and AI products with confidence and at scale.
We'll trust you to:
  • Design, build, and maintain scalable data pipelines that support data collection, annotation, training, evaluation, analytics, and reporting workflows.
  • Develop and operate systems for dataset management, storage, versioning, and lifecycle governance to ensure reliable and reproducible AI workflows.
  • Implement monitoring, observability, and alerting capabilities that provide visibility into data quality, system health, and operational performance.
  • Build dashboards, tooling, and self-service capabilities that improve transparency, efficiency, and decision-making across data operations.
  • Partner with Product, Engineering, and Data teams to evolve the infrastructure and platforms supporting AI-enabled products and workflows.
  • Identify bottlenecks and opportunities for automation, delivering scalable solutions that improve reliability, consistency, and operational efficiency.

You'll need to have:
  • Bachelor's degree in Finance, Business, Economics, Accounting, STEM or degree-equivalent qualifications
  • 3+ years in data engineering (Python, SQL)
  • Experience building ETL/data pipelines at scale and creating data collection frameworks for structured and unstructured data
  • Experience with data modeling and developing proactive data quality strategies that ensure data is fit for purpose
  • Experience working with ML/AI datasets or experimentation workflows.
  • Excellent problem-solving and analytical thinking skills with strong attention to detail.
  • Proven track record of stakeholder relationship management, communication, and cross-team collaboration.

We'd love to see:
  • Keen interest in and familiarity with generative AI frameworks and the requirements of Agentic AI.
  • Experience in semantic structures or large scale data modeling
  • Experience using data visualization tools such as Tableau, QlikSense, or PowerBI
  • Experience developing or managing annotation programs and training/evaluation datasets for ML or NLP models.
  • Deep domain expertise in financial markets/news and understanding of our customers' needs.

If this sounds like you:
Apply! If you think we're a good match. We'll get in touch to let you know the next steps!
Salary Range = 110,000 - 190,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

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Hours and flexibility

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About Bloomberg

Sourced by ZipRecruiter

Bloomberg runs on data. As the Data Management & Analytics team within Engineering, we support our organization's needs around managing data efficiently. The vision of the team is to build solutions that drive data quality, data dictionary, data stewardship, data lineage, reference, and master data management across various data domains (prospect, customer, vendor, material etc.). We partner with business teams across the organization in addressing their data needs and ultimately helping run business operations efficiently and make improved decisions.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1981

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