ZipRecruiter

Log In

1

Assistant Ai Labeling Jobs (NOW HIRING)

Tt

AI & Computer Vision Intern

New York, NY

... in 3D space. * Assist in developing and refining labeling guidelines, class definitions, and ... Computer vision and AI: basic understanding of common model types (e.g., CNNs, UNet, Faster RCNN ...

General Motors

Senior AI/ML Engineer

Sunnyvale, CA · On-site

$122K - $168K/yr

... labeling at scale. * Champion AI-assisted engineering Use and advocate for modern AI-powered development workflows (code assistants, automated documentation, test generation, etc.) to increase ...

General Motors

Senior AI/ML Engineer

Sunnyvale, CA · On-site +1

$124K - $170K/yr

... labeling at scale. * Champion AI-assisted engineering Use and advocate for modern AI-powered development workflows (code assistants, automated documentation, test generation, etc.) to increase ...

next page

Showing results 1-20

People also search for

All JobsAi Labeling JobsAssistant Ai Labeling Jobs

Assistant Ai Labeling information

See salary details

$29K

$48.4K

$69.5K

How much do assistant ai labeling jobs pay per year?

As of Jun 8, 2026, the average yearly pay for assistant ai labeling in the United States is $48,396.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,000.00 and $48,500.00 per year, depending on experience, location, and employer.

What is the difference between Assistant Ai Labeling vs Data Annotator?

AspectAssistant Ai LabelingData Annotator
CredentialsHigh school diploma or equivalent; some roles may require basic technical skillsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentRemote or office-based; collaborative with AI teamsPrimarily remote; focused on data labeling tasks
Industry UsageAI development, machine learning projectsData preparation for AI, machine learning, and analytics
Search & Comparison IntentUnderstanding roles supporting AI trainingData labeling and annotation tasks for AI models

Assistant Ai Labeling involves supporting AI systems by labeling data, often requiring some technical understanding. Data Annotator focuses on labeling data to prepare datasets for AI training. Both roles are essential in AI development, with overlapping skills but different focus areas.

What are Assistant AI Labeling jobs?

Assistant AI Labeling jobs involve reviewing, tagging, and categorizing data such as images, text, or audio to help train artificial intelligence and machine learning models. These roles are essential because accurate labeling ensures that AI systems can learn to recognize patterns and make decisions effectively. Tasks may include drawing bounding boxes around objects in images, transcribing spoken words, or classifying text according to given guidelines. The work is often done using specialized software and requires attention to detail as well as consistency. Assistant AI Labelers may work remotely or in-house for tech companies, research organizations, or data annotation firms.

What are some common challenges faced by Assistant AI Labeling professionals, and how can they be addressed?

Assistant AI Labeling professionals often encounter challenges such as maintaining consistency and accuracy when labeling large volumes of data, especially with ambiguous or subjective cases. To address these challenges, most teams implement clear annotation guidelines, regular training sessions, and peer review processes to ensure high-quality outputs. Collaboration with data scientists and project managers is also key, as open communication helps clarify uncertainties and align labeling practices with project goals. Embracing feedback and staying flexible as guidelines evolve can further enhance both the quality of work and job satisfaction in this role.

What are the key skills and qualifications needed to thrive as an Assistant AI Labeling Specialist, and why are they important?

To thrive as an Assistant AI Labeling Specialist, you need strong attention to detail, accuracy, and an understanding of data annotation practices, often supported by a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools, and sometimes basic knowledge of programming languages like Python is beneficial. Dependability, time management, and the ability to follow complex instructions are crucial soft skills for excelling in this role. These skills ensure high-quality labeled data, which is vital for training accurate and reliable AI models.
More about Assistant Ai Labeling jobs
What cities are hiring for Assistant Ai Labeling jobs? Cities with the most Assistant Ai Labeling job openings:
What are the most commonly searched types of Ai Labeling jobs? The most popular types of Ai Labeling jobs are:
What states have the most Assistant Ai Labeling jobs? States with the most job openings for Assistant Ai Labeling jobs include:
What job categories do people searching Assistant Ai Labeling jobs look for? The top searched job categories for Assistant Ai Labeling jobs are:
Assistant Ai Labeling jobs near you
Infographic showing various Assistant Ai Labeling job openings in the United States as of May 2026, with employment types broken down into 96% Full Time, 2% Part Time, and 2% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $48,396 per year, or $23.3 per hour.
AI & Computer Vision Intern

AI & Computer Vision Intern

Thornton Tomasetti, Inc.

New York, NY • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago

Job description

Thornton Tomasetti applies engineering and scientific principles to solve the world's challenges. An independent organization of creative thinkers and innovative doers collaborating from offices worldwide, our mission is to bring our clients' ideas to life and, in the process, lay the groundwork for a better, more resilient future. We provide support and opportunities to our employees to achieve their full potential and cultivate a rewarding career.
Our Forensics team works on a wide range of projects involving the built environment, using engineering analysis, data, and technology to help clients understand conditions, evaluate performance, and make informed decisions. As we expand our use of AI and computer vision, we are developing and maintaining datasets and tools that help analyze images and 3D data from structures, and this role will directly support those efforts.
The Role:
We have an opportunity for an AI & Computer Vision Intern for our Forensics Practice.
Responsibilities:
  • Support the AI/ML team in labeling and curating datasets for computer vision models, including classification, object detection, instance segmentation, and semantic segmentation.
  • Work with 2D image datasets (e.g., photos, drone imagery, plan drawings) to draw and review labels for objects and damage types.
  • Work with 3D point cloud models (e.g., structural frames, industrial facilities) to segment and label structural components and other features in 3D space.
  • Assist in developing and refining labeling guidelines, class definitions, and attribute schemas to improve consistency and model performance.
  • Perform quality assurance (QA/QC) on existing labels, identify labeling errors or ambiguities, and suggest corrections and improvements.
  • Help the engineering team prepare example datasets, figures, and visualizations for internal presentations, reports, and publications related to AI model development.
  • Assist in basic data pre-processing and organization (e.g., dataset splitting, file naming, simple scripting) to support experimentation and model training workflows.
  • Collaborate with forensic engineers to understand model objectives and failure modes, and adjust labeling strategies accordingly (e.g., edge cases, hard negatives).

Requirments:
  • Computer vision and AI: basic understanding of common model types (e.g., CNNs, U-Net, Faster R-CNN, YOLO) and tasks (classification, detection, segmentation).
  • Programming and data tools: Python and/or MATLAB for simple data manipulation, visualization, and experiment tracking.
  • Point cloud software: CloudCompare or other point cloud viewing and manipulation software for slicing, filtering, and annotating 3D datasets.
  • Labeling platforms: experience with image or point cloud annotation tools (e.g., Supervisely, CVAT, Labelbox, or similar).
  • A strong interest in applying AI and computer vision to structural and forensic engineering problems is essential.

Compensation
The rate for this position generally is $1 - $400 hourly. This range is a good faith estimate provided pursuant to the New York Pay Transparency Law. It is based on what a successful New York applicant might be paid and assumes that the successful candidate will be in New York or perform the position from New York. Similar positions located outside of New York will not necessarily receive the same compensation. Actual pay rates may vary from the range, as permitted by New York Equal Pay Transparency Law. Compensation offers will be based on various factors, including operational needs, individual education, qualifications and experience, work location and comparison to employee already in the role, as well as other considerations permitted by law. A potential new employee's pay history will not be used in compensation decisions.
Benefits
Depending on your employment status, benefits may include:
  • Medical, Dental, Vision, Life, AD&D, Disability and other voluntary benefits
  • Flexible Spending Accounts for Medical and Childcare
  • Paid Time Off, Family Leave for New Parents, Volunteer Time
  • Tuition Reimbursement
  • Commuter Transit (where available)
  • 401k retirement savings with Company matching on employee contributions and/or qualified student loan repayments
  • Fitness Reimbursement
  • And other various wellness, diversity/inclusion and employee resource programs and initiatives

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Thornton Tomasetti is proud to be an equal employment workplace. Individuals seeking employment at Thornton Tomasetti are considered without regards to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by federal, state, or local laws.
Thornton Tomasetti Global Terms of Use and Privacy Statement
Carefully read these Terms of Use before using this website. Your access to and use of this website and application for a job at Thornton Tomasetti are conditioned on your acceptance and compliance with these terms.
Please access the linked document by clicking here, select the country where you are applying for employment, and review. Before submitting your application you will be asked to confirm your agreement with the terms.
To request a reasonable accommodation during the application process for this role, please contact talentconcierge@throntontomasetti.com
Beware Of Recruitment Fraud: Scammers may attempt to impersonate Thornton Tomasetti. Messages from our firm come only from the ThorntonTomasetti.com domain, Thornton Tomasetti does not use any third-party recruiters. When in doubt, please contact us through our web form here and see how you can protect yourself online here.

Apply