Computer Vision Intern Jobs in New York (NOW HIRING)

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 preprocessing 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, UNet, Faster RCNN, 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-$400hourly.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 byNew YorkEqual 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 SanFrancisco 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.