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Image Labeling Remote Jobs in Georgia (NOW HIRING)

Bright Vision Technologies

AI Data Engineer

Norcross, GA · Remote

$100K - $150K/yr

AI Data Engineer Location: 100% Remote (Continental United States) Position Type: In-house Bright ... Implement labeling workflows, active learning pipelines, and human-in-the-loop data improvement ...

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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 are popular job titles related to Image Labeling Remote jobs in Georgia? For Image Labeling Remote jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Image Labeling Remote jobs in Georgia look for? The top searched job categories for Image Labeling Remote jobs in Georgia are:
What cities in Georgia are hiring for Image Labeling Remote jobs? Cities in Georgia with the most Image Labeling Remote job openings:
Image Labeling Remote jobs near you

AI Data Engineer

Bright Vision Technologies

Norcross, GA • Remote

$100K - $150K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Bright Vision Technologies is a forward-thinking software development company dedicated to building innovative solutions that help businesses automate and optimize their operations. We leverage cutting-edge technologies to create scalable, secure, and user-friendly applications.
As we continue to grow, we’re looking for a skilled AI Data Engineer to join our dynamic team and contribute to our mission of transforming business processes through technology. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
 AI Data EngineerJob Title: AI Data Engineer
Location: 100% Remote (Continental United States)
Position Type: In-house Bright Vision Technologies SOW engagement (no third-party client or vendor)
Experience: 6+ years
Salary Range : $100k to $150k per annnum
Sponsorship: No new H1B sponsorship available. H1B transfers welcomed for qualified candidates.
Employment Type: Full-time, direct W2 with Bright Vision Technologies (no C2C, no 1099, no third-party)
Engagement: Long-term, multi-year, aligned to the Bright Vision SOW delivery roadmap
Compensation: Competitive base salary commensurate with experience, plus benefits.
Employment Terms & Visa Policy
This is a 100% remote, full-time, direct W2 position with Bright Vision Technologies.
This role is part of Bright Vision Technologies’ in-house Statement of Work (SOW) engagement. The client, end customer, and employer for this position is Bright Vision Technologies — there is no third-party client, vendor, or implementation partner involved.
We do not engage in C2C, 1099, or third-party arrangements for this role.
BUT STRICTLY NO C2C/1099/3RD PARTY COMPANIES. ALL OUR ROLES ARE W2 AND NO 3RD PARTY BROKERING PLEASE.
Candidates must be willing to work directly as a full-time W2 employee of Bright Vision Technologies and contribute to our in-house SOW deliverables.
No new H1B sponsorship is available for this role.
However, candidates who are currently on a valid H1B visa and require a transfer are welcome to apply. We will support H1B transfers for qualified candidates.
For every role, a technical coding assessment is mandatory. Please apply only if you are confident in your technical abilities and hands-on experience.
Job Summary
We are seeking an AI Data Engineer to build and operate the large-scale data systems that power modern AI training and evaluation pipelines. The role combines deep data engineering expertise with a strong understanding of AI workloads, focusing on ingestion, transformation, quality assurance, lineage, and high-throughput delivery of data to training jobs across diverse modalities. The ideal candidate has experience operating petabyte-scale data systems, strong software engineering fundamentals, and clear understanding of how data infrastructure choices propagate into model quality and training efficiency.
Key Responsibilities
  • Design and operate large-scale data pipelines supporting AI training, evaluation, and continual improvement workflows.
  • Build ingestion systems for diverse modalities including text, image, audio, video, and structured signals.
  • Implement data cleaning, deduplication, filtering, and quality assurance at petabyte scale.
  • Develop dataset versioning, lineage, and provenance tracking systems suitable for reproducible training.
  • Build high-throughput data loading systems that maximize GPU utilization during training.
  • Implement labeling workflows, active learning pipelines, and human-in-the-loop data improvement systems.
  • Design storage architectures balancing cost, throughput, and latency across data tiers.
  • Build evaluation dataset construction pipelines with strict integrity and contamination controls.
  • Implement data privacy, redaction, and consent enforcement throughout the pipeline.
  • Collaborate with ML researchers and engineers to align data systems with model development needs.
  • Drive observability of data quality, drift, and pipeline health across the AI data estate.
  • Optimize cost and performance through compression, format selection, and caching strategies.
  • Document data systems, schemas, and operational procedures for broad internal use.
  • Stay current with AI data infrastructure research and emerging open-source tools.
Required Qualifications
  • Bachelor’s or Master’s degree in Computer Science or a related field.
  • Six or more years of data engineering experience, with significant work supporting ML or AI workloads.
  • Strong proficiency in Python and at least one JVM or systems language.
  • Deep experience with modern data processing frameworks such as Spark, Ray, or Beam.
  • Hands-on experience operating petabyte-scale storage and pipeline systems.
  • Strong understanding of distributed systems, data modeling, and storage formats.
  • Experience with dataset versioning, lineage, and reproducibility for ML workflows.
  • Familiarity with high-throughput data loading for accelerator-based training.
  • Strong software engineering practices including testing, CI/CD, and code review.
  • Excellent communication and cross-functional collaboration skills.
Preferred Qualifications
  • Experience with multimodal datasets at large scale.
  • Familiarity with data quality tooling and dataset evaluation methodology.
  • Exposure to privacy-preserving data systems and regulated data handling.
  • Open-source contributions to data infrastructure projects.
  • Experience supporting frontier model training pipelines.

How to Apply
Would you like to know more about this opportunity?
For immediate consideration, please send your resume to jaya@bvteck.com or contact us at (908) 505-3545. Learn more about Bright Vision Technologies at www.bvteck.com.
We recognize that our people are our strength, and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company.We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
Bright Vision Technologies is an Equal Opportunity Employer, including Disability/Veterans.
Position offered by “No Fee Agency.”

Equal Employment Opportunity (EEO) Statement

Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.

BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees\' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

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