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Internship Ai Annotation Jobs (NOW HIRING)

Hatch IT

NLP/Linguistics Software Engineer

Somerville, MA

$125K - $150K/yr

... internships or projects). * Proficiency in Java (our core analytics language) or Python (for AI/ML ... Experience with data quality evaluation, data annotation, or guideline design, preferably for ...

Babel Street

NLP/Linguistics Software Engineer

Somerville, MA · On-site

$125K - $150K/yr

... internships or projects). * Proficiency in Java (our core analytics language) or Python (for AI/ML ... Experience with data quality evaluation, data annotation, or guideline design, preferably for ...

Babel Street

NLP/Linguistics Software Engineer

Somerville, MA · On-site

$125K - $150K/yr

... internships or projects). * Proficiency in Java (our core analytics language) or Python (for AI/ML ... Experience with data quality evaluation, data annotation, or guideline design, preferably for ...

Valeo

Software Engineer

San Mateo, CA

$96K - $156K/yr

... and AI Display Smartglasses. * Brainstorm innovative new user experiences that can unleash the ... Define and conduct data gathering and annotation activities to support software development and ...

Valeo

Software Engineer

San Mateo, CA · On-site

$96K - $156K/yr

... and AI Display Smartglasses. * Brainstorm innovative new user experiences that can unleash the ... Define and conduct data gathering and annotation activities to support software development and ...

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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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Internship Ai Annotation jobs near you
Infographic showing various Internship Ai Annotation job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution.
NLP/Linguistics Software Engineer

NLP/Linguistics Software Engineer

Hatch IT

Somerville, MA

$125K - $150K/yr

Full-time

Posted 19 days ago

Job description

hatch I.T. is partnering with Babel Street to find an NLP/Linguistics Software Engineer. Please see details below:

About the Role

Babel Street is looking for a Software Engineer to join their Analytics Group. This is an execution-focused "builder" role for an engineer early in their career who wants to work at the intersection of NLP algorithms, search engines, and data science techniques. In this role, you will help create the next generation of architecture and components for their analytics platform, focusing specifically on their record matching functionality. You will bridge the gap between linguistic theory and practical AI applications, helping us implement practical, innovative text analytics and AI-driven features. You will work closely with senior engineers to learn how to deliver software that is safe, reliable, and production-ready.

About the Company

Babel Street is the trusted technology partner for the world's most advanced identity intelligence and risk operations. They deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360-degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empowers government and commercial organizations to transform high-stakes identity and risk operations into a strategic advantage.  The actionable insights we deliver safeguard lives and protect critical assets around the world.  Babel Street is headquartered in Reston, Virginia, with regional offices in Boston, MA and Cleveland, OH, and international offices in Australia, Canada, Israel, Japan, and the U.K.

What you will do:
  • Implement and Maintain: Write high-quality, maintainable code to support the analytics platform and its record matching components.
  • Bridge Theory and Practice: Take theoretical ideas from linguistics and data science and implement them as practical software features.
  • Support Search Internals: Help optimize and maintain search engine components, including Elasticsearch data modeling and performance tuning.
  • Collaborate and Learn: Participate in agile sprint planning and work daily with senior partners to translate project requirements into technical solutions.
  • Build Scalable Systems: Assist in designing and shipping robust APIs and scalable architectures that integrate into our AI-native platform.
What you will bring:

Required:

  • 2-4 years of professional software engineering experience (including high-impact internships or projects).
  • Proficiency in Java (our core analytics language) or Python (for AI/ML integrations).
  • Problem Solver: Ability to work across teams and make steady progress in ambiguous problem spaces.
  • Educational Foundation: Bachelor's degree in Computer Science, Linguistics, or a related technical field.

Preferred (Nice to Have):

  • Foundation in Data Science: Experience with data quality evaluation, data annotation, or guideline design, preferably for linguistics.
  • Familiarity with Elasticsearch internals or other search/retrieval-based systems.
  • Exposure to computational linguistics or natural language processing (NLP).
  • Interest in Kubernetes and cloud-native architectures.
What success looks like:
  • Month 1-2: Ramp up on the analytics stack and record matching architecture; ship your first initial changes to production.
  • Month 3-4: Take ownership of a specific component or pipeline improvement with guidance, including full testing and documentation.
  • Month 5-6: Deliver a measurable improvement to record matching quality or pipeline reliability and contribute to team design discussions.
Why this role matters:
The record matching functionality is where Babel Street's signals become usable intelligence. Do you care about provenance, explainability, and trust? When a match decision affects whether someone is onboarded or investigated, "the model said so" is not good enough. You will help build systems where every match is defensible, auditable, and tunable - a rare luxury in modern ML-heavy stacks. Do you speak multiple languages? Since our platform processes data from around the globe, your linguistic insights can directly inform how we build and polish the NLP and computational linguistics components that make our record matching world-class.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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