ZipRecruiter

Log In

1

From Home Image Segmentation Jobs (NOW HIRING)

next page

Showing results 1-20

All JobsFrom Home Image Segmentation Jobs

From Home Image Segmentation information

See salary details

$759

$2.1K

$3.1K

How much do from home image segmentation jobs pay per week?

As of Jul 1, 2026, the average weekly pay for from home image segmentation in the United States is $2,116.79, according to ZipRecruiter salary data. Most workers in this role earn between $1,557.69 and $2,634.62 per week, depending on experience, location, and employer.

What is the difference between From Home Image Segmentation vs From Home Data Annotation?

AspectFrom Home Image SegmentationFrom Home Data Annotation
Primary FocusSegmenting images into meaningful partsLabeling data points or objects in images
Required SkillsComputer vision, image processing, annotation toolsData labeling, attention to detail, annotation software
Work EnvironmentRemote, flexible, tech-focusedRemote, flexible, data-driven
Industry UsageAI, machine learning, autonomous vehiclesAI, machine learning, data training

From Home Image Segmentation involves dividing images into segments for AI training, requiring technical skills in image processing. From Home Data Annotation focuses on labeling data for machine learning, emphasizing accuracy in data labeling. Both roles are remote, industry-specific, and essential for AI development, but they differ in technical complexity and focus areas.

More about From Home Image Segmentation jobs
What cities are hiring for From Home Image Segmentation jobs? Cities with the most From Home Image Segmentation job openings:
What are the most commonly searched types of Image Segmentation jobs? The most popular types of Image Segmentation jobs are:
What states have the most From Home Image Segmentation jobs? States with the most job openings for From Home Image Segmentation jobs include:
What job categories do people searching From Home Image Segmentation jobs look for? The top searched job categories for From Home Image Segmentation jobs are:
From Home Image Segmentation jobs near you
Infographic showing various From Home Image Segmentation job openings in the United States as of June 2026, with employment types broken down into 6% As Needed, 18% Full Time, 64% Part Time, and 12% Contract. Highlights an 77% Physical, 1% Hybrid, and 22% Remote job distribution, with an average salary of $110,073 per year, or $52.9 per hour.
NIST PREP Postdoctoral Research Engineer

NIST PREP Postdoctoral Research Engineer

Southeastern Universities Research Association

Gaithersburg, MD • On-site

$80K - $90K/yr

Full-time

Posted 14 days ago

Job description

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.
Research Title: Research Engineer
The work will entail: The candidate will join a multidisciplinary team of scientists working to advance nondestructive defect detection metrology for advanced semiconductor packaging by developing reference artifacts and benchmark datasets. The candidate will contribute to designing CAD models, running X-ray computed tomography (XCT) simulations, and performing XCT reconstructions to generate datasets. The candidate will develop a Python script or package to automate these processes. Additionally, the candidate will utilize a generative modeling process created by the team to help generate 3D models with seeded defects. The datasets will be used to evaluate defect detection and image segmentation algorithms, including those based on deep learning principles. The candidate may contribute to sample preparation and nondestructive and destructive measurements. The incumbent will analyze the resulting measurements, perform image processing, and extract meaningful information to support the research goals outlined in the experiment plan. They will organize the measured and analyzed datasets for publication, communicate with the team, and share the results at conferences and in publications.
Key responsibilities will include, but are not limited to:
  • Design 3D models for simulation, run XCT simulations, carry out XCT reconstruction, and execute image analysis.
  • Organize and prepare data sets for publication.
  • Prepare samples and make nondestructive and destructive measurements.
  • Presenting results at internal meetings and occasional meetings with external stakeholders.
  • Publish results in journals and present results at conferences.

Qualifications
  • A doctoral degree in physics, engineering, or a related discipline.
  • Experience with XCT measurements, reconstruction, and image analysis. Experience with XCT simulation is a plus.
  • Experience in writing Python scripts. Familiarity with automating or controlling other software, tools, or processes through APIs, inter-process communication, or similar methods is a plus.
  • Experience with sample preparation (mechanical polishing, focused ion beam) or scanning electron microscopy imaging is a plus.
  • Experience with implementing deep learning-based image segmentation processes is a plus.
  • Strong oral and written communication skills.
  • Able to quickly learn and adapt to new fields or techniques

Privacy Act StatementAuthority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate the administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated. By applying to a CHIPS-funded PREP opportunity, you also acknowledge that participation in the project requires signing a Non-Disclosure Agreement (NDA) prior to beginning any work.
SURA is an Equal Opportunity Employer. We believe that no one should be discriminated against because of their differences, such as age, disability, ethnicity, gender, gender identity and expression, religion, or sexual orientation. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status, or any other basis as protected by federal, state, or local law.
PREP0004829

Apply