2

Image Labeling Remote Jobs in Ohio (NOW HIRING)

Software Engineer, Senior

Dayton, OH ยท On-site +1

$119K - $157K/yr

Background in signal processing, image processing, or remote sensing data workflows. * Experience ... Familiarity with ML/Ops practices - training pipelines, data labeling, model evaluation, and ...

Software Engineer, Senior

Dayton, OH ยท On-site +1

$119K - $157K/yr

Background in signal processing, image processing, or remote sensing data workflows. * Experience ... Familiarity with ML/Ops practices -- training pipelines, data labeling, model evaluation, and ...

Image Labeling Remote information

What is image labeling in a remote job?

Image labeling in a remote job involves tagging or annotating images with relevant information or categories from your home or any location outside of a traditional office. This process helps train machine learning models to recognize objects, people, or scenes within images. Remote image labelers use specialized software to identify and mark features according to project guidelines. The work is often flexible and may be paid per task or per hour, depending on the employer.

How much do AI labelers make?

AI labelers, including those working remotely in image labeling roles, typically earn between $10 and $20 per hour, depending on experience and the company. Many remote positions offer flexible schedules and may pay per task or image labeled rather than hourly.

What is the salary of image Labelling job?

The salary for an image labeling remote job typically ranges from $10 to $20 per hour, depending on experience, the company, and the complexity of the labeling tasks. Many positions are paid hourly or per task, and some may offer bonuses for accuracy or speed.

How can I make 2000 a week working from home?

In remote image labeling jobs, earning $2000 weekly typically requires working full-time hours, often around 40 hours per week, and completing high volumes of labeled images with accuracy. Success depends on experience, efficiency, and the pay rate per task, which varies by platform and project complexity. Building skills in image annotation tools and maintaining consistent productivity can help increase earnings to reach that goal.

What is the difference between Image Labeling Remote vs Data Annotation Specialist?

AspectImage Labeling RemoteData Annotation Specialist
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote or on-site, flexible hours
Industry UsageAI, machine learning, computer visionAI, machine learning, data processing
Search & Comparison IntentOften compared for similar data labeling rolesRelated role in data preparation

Image Labeling Remote and Data Annotation Specialist roles both involve preparing data for AI systems, often working remotely with similar skills. However, Image Labeling Remote typically focuses specifically on labeling images and visual data, while Data Annotation Specialist may include a broader range of data types like text or audio. Both roles are essential in AI development and share similar work environments and skill requirements.

What are the key skills and qualifications needed to thrive as an Image Labeling Remote worker, and why are they important?

To thrive as an Image Labeling Remote worker, you need strong attention to detail, basic computer literacy, and familiarity with data annotation concepts, often supported by a high school diploma or equivalent. Proficiency with image labeling platforms such as Labelbox, Supervisely, or proprietary annotation tools is typically required. Reliability, self-motivation, and the ability to follow precise instructions make someone stand out in this position. These skills ensure that labeled data is accurate and consistent, which is crucial for training high-quality machine learning models.

What are some common challenges faced by remote image labeling professionals, and how can they be managed?

Remote image labeling professionals often encounter challenges such as maintaining focus during repetitive tasks, ensuring high accuracy, and communicating effectively with team members across different time zones. To manage these, it's helpful to set up a dedicated, distraction-free workspace, take regular breaks to prevent fatigue, and use collaboration tools like Slack or project management platforms to stay connected with the team. Adhering closely to labeling guidelines and participating in regular quality reviews also help maintain accuracy and consistency.

How to make $1000 a week remote?

To make $1000 a week as an image labeler remotely, you need to complete a high volume of accurate labeling tasks, often working for multiple platforms or clients simultaneously. Building experience, improving efficiency, and using tools like labeling software can help increase earnings, but consistent high-quality work is essential to reach that income level.
What cities in Ohio are hiring for Image Labeling Remote jobs? Cities in Ohio with the most Image Labeling Remote job openings:

Software Engineer, Senior

GRVTY

Dayton, OH โ€ข On-site, Remote

$119K - $157K/yr

Other

Posted 7 days ago


Job description

What Impact You'll Have

GRVTY is looking for a Senior Software Engineer to join a small, technically focused team supporting national security missions at a customer site in Dayton, Ohio. This is hands-on engineering work - you will be designing and building Python-based software tools that support optical signature modeling, spectral data analysis, and machine learning-enabled sensor workflows. The work spans algorithm development, data pipeline construction, and integration of ML capabilities into operational and analytical environments.

You will work directly with scientists, sensor domain experts, and intelligence analysts - translating complex technical requirements into functional, maintainable software. This is not a role for someone looking to coast. We want someone who is technically sharp, can operate with a degree of autonomy, and understands that the software they build has real downstream impact on mission outcomes.

What You'll be Owning

  • Design, develop, and maintain Python-based software tools supporting optical signature modeling, spectral sensor data processing, and analytical workflows.
  • Work with sensor physicists, data scientists, and machine learning engineers to translate technical concepts and mission requirements into working software.
  • Build and optimize data pipelines for ingesting, processing, and analyzing large-scale scientific and sensor datasets.
  • Develop and integrate machine learning workflows - including training data preparation, model integration, and evaluation - into operational toolsets.
  • Create clear software architecture documentation, workflow diagrams, and code structure so tools can be maintained, extended, and transitioned effectively.
  • Test, validate, and troubleshoot algorithms and software modules across development and deployment environments, including classified workspaces.
  • Manage and maintain Git repositories with discipline - clean commits, meaningful documentation, and reproducible builds.
  • Contribute to a culture of technical rigor: peer reviews, coding standards, and honest engagement with complex problems.

What You Must Have

  • Active TS/SCI clearance with ability to obtain CI polygraph.
  • Bachelor's degree in Computer Science, Engineering, Physics, Mathematics, Data Science, or a related STEM field. Equivalent hands-on experience will be considered.
    • 9+ years of professional software development experience, with demonstrated focus on scientific computing, algorithm development, data processing, or related technical domains or 7+ years of experience and a Masters degree
  • Expert-level Python programming, including object-oriented design, modular architecture, and production-quality code.
  • Experience developing software for data-intensive workflows - sensor data, scientific data, simulation, or equivalent.
  • Ability to work from technical or scientific requirements and produce well-structured software architecture, logic flows, and implementation plans.
  • Comfortable operating in both Windows and Linux environments, including secure or classified customer workspaces.
  • Familiarity with source control and development tooling: Git, GitLab, Bitbucket, Jira, Jenkins, or equivalent.
  • Strong communication skills - able to work directly with domain experts who are not software engineers and translate what they need into software that actually works.

What Would be Nice to Have

  • Experience with optical signature modeling, EO/IR sensor data, spectral analysis, or hyperspectral data processing.
  • Familiarity with machine learning frameworks and workflows: PyTorch, TensorFlow, scikit-learn, or equivalent.
  • Experience with scientific Python libraries: NumPy, pandas, OpenCV, SciPy, or similar.
  • Background in signal processing, image processing, or remote sensing data workflows.
  • Experience with simulation, modeling, or mission analysis software in a defense or intelligence context.
  • Familiarity with ML/Ops practices - training pipelines, data labeling, model evaluation, and deployment workflows.
  • Experience integrating algorithms into existing operational software suites.
  • Proficiency in a secondary technical language: C, C++, MATLAB, Java, or Rust.
  • Advanced degree in a relevant technical field (Computer Science, Electrical Engineering, Physics, Image Science, or related).
  • Prior experience supporting defense, intelligence, or classified customer environments.
  • Experience with CI/CD practices, automated testing, and DevSecOps tooling.