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Remote Data Labeling Jobs in Massachusetts (NOW HIRING)

General Motors

Senior AI/ML Engineer

Boston, MA · On-site +1

$113K - $155K/yr

Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA ... The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ...

Jj

Regulatory Affairs Specialist I - Spine

Raynham, MA · On-site +1

There is no full-time remote option. Key Responsibilities: * Provides regulatory guidance to ... Defines data and information needed for regulatory marketing authorizations. * Develops labeling ...

Lavendo

Technical Product Manager (Voice AI)

Boston, MA · Remote

$120K - $150K/yr

Drive product decisions using data, partner feedback, and competitive analysis * Work cross ... Remote-first flexibility; work ET hours on your terms * Real decision-making authority with ...

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Remote Data Labeling information

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How much do remote data labeling jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for remote data labeling in Massachusetts is $36.85, according to ZipRecruiter salary data. Most workers in this role earn between $18.31 and $49.77 per hour, depending on experience, location, and employer.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform or employer. Many remote data labeling jobs are paid per task or project, which can affect overall earnings, and some roles may require basic skills in data annotation tools or image/video labeling software.

How can I make 2000 a week working from home?

Remote data labeling jobs typically pay per task or hour, with earnings varying based on experience, efficiency, and the number of tasks completed. To make $2,000 weekly, you would need to consistently complete a high volume of labeled data, often requiring strong attention to detail and familiarity with labeling tools. Achieving this income level may also involve working multiple platforms or combining data labeling with other remote tasks.

How to make $1000 a week remote?

Remote data labeling jobs typically pay per task or hour, with earnings varying based on experience, efficiency, and the volume of work completed. To make $1000 weekly, you need to consistently complete a high number of labeled data sets, often requiring strong attention to detail and familiarity with labeling tools. Building a reputation and working with multiple platforms can help increase your income potential.

What are some common challenges faced by remote data labelers, and how can they be managed?

Remote data labelers often face challenges such as maintaining focus during repetitive tasks, managing volume-based workloads, and interpreting ambiguous data with consistency. To manage these, it's important to set up a distraction-free workspace, take regular breaks to avoid fatigue, and seek clarification from supervisors or project guidelines when uncertainties arise. Most companies provide onboarding and ongoing support to help new labelers understand annotation standards and best practices. Collaborating with remote team members via chat or project management platforms also helps maintain quality and stay connected. By being proactive and utilizing available resources, remote data labelers can maintain high accuracy and productivity.

Is data labelling a good career?

Data labeling is a common entry-level role in the AI and machine learning industries, involving annotating data to train algorithms. It offers flexible schedules and requires attention to detail, but typically has lower pay and limited advancement opportunities compared to other tech roles.

What are the key skills and qualifications needed to thrive in the Remote Data Labeling position, and why are they important?

To thrive as a Remote Data Labeling specialist, you need strong attention to detail, basic data analysis skills, and the ability to accurately tag and categorize diverse data types, often with a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools (such as Labelbox or Amazon SageMaker Ground Truth), and, occasionally, basic knowledge of data privacy standards is helpful. Time management, self-discipline, and effective remote communication are valuable soft skills in this position. These skills ensure that labeled data is accurate and reliable, supporting the success of machine learning and AI projects.

What is a Remote Data Labeling job?

A Remote Data Labeling job involves annotating or categorizing data, such as images, text, audio, or video, to train machine learning models. Workers review and tag content based on specific guidelines provided by companies. This job is typically done online from home and requires attention to detail, consistency, and sometimes specialized domain knowledge. It plays a crucial role in improving artificial intelligence systems by providing high-quality labeled data.

What are the most commonly searched types of Data Labeling jobs in Massachusetts? The most popular types of Data Labeling jobs in Massachusetts are:
What are popular job titles related to Remote Data Labeling jobs in Massachusetts? For Remote Data Labeling jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Remote Data Labeling jobs in Massachusetts look for? The top searched job categories for Remote Data Labeling jobs in Massachusetts are:
What cities in Massachusetts are hiring for Remote Data Labeling jobs? Cities in Massachusetts with the most Remote Data Labeling job openings:
Remote Data Labeling jobs near you
Ophthalmologist (Medical Data Labeling Specialist)

Ophthalmologist (Medical Data Labeling Specialist)

Saviance

Boston, MA • Remote

Other

Posted 16 days ago

Job description

Ophthalmologist (Medical Data Labeling Specialist)
Location: India, Remote
Duration: Ongoing Part-Time
About BigRio
BigRio is a Boston-based, remote-first technology consulting firm specializing in advanced data and software solutions. We partner with forward-thinking organizations to deliver scalable, cost-effective, and innovative technology, with particular expertise in AI/ML, data engineering, and cloud-native applications. Our clients span healthcare, life sciences, government, and enterprise sectors, and we are known for our ability to tackle complex challenges with cutting-edge solutions.
About Job:
This role leverages the clinical expertise of an ophthalmologist to accurately annotate and label medical data, primarily images and structured clinical data related to eye health, for the development and refinement of artificial intelligence (AI) and machine learning (ML) models in ophthalmology.
Responsibilities
Key responsibilities include:
  • Data Annotation: Reviewing and annotating various ophthalmic data like fundus images, Optical Coherence Tomography (OCT) scans, and other visual data, identifying anatomical structures and disease markers.
  • Adherence to Protocols: Applying standardized grading protocols consistently for accurate and consistent labeling.
  • Quality Control & Feedback: Participating in calibration sessions and reviews to maintain annotation consistency.
  • Collaboration: Working with AI engineers and data scientists to ensure the clinical validity of guidelines.
  • AI Model Validation: Validating AI model outputs for clinical accuracy and safety.
  • Patient Education Material Development (potential): Possibly creating or reviewing materials for AI/ML algorithms to provide accurate patient education.
  • Privacy and Security: Ensuring compliance with patient privacy and data security policies, like HIPAA.
Qualifications
Essential qualifications typically include:
  • Ophthalmologist (MBBS) with at least 1-2 years of clinical experience.
  • Extensive Clinical Knowledge: In-depth understanding of various eye conditions.
  • Experience in Clinical Data Review: Familiarity with medical record documentation.
  • Attention to Detail: Commitment to accurate annotation.
  • Communication Skills: Excellent communication skills, both written and verbal, in English.
  • Teamwork: Ability to collaborate effectively with a multidisciplinary team.
Required skills often include:
  • Medical Image Annotation: Proficiency in using annotation tools to delineate structures and pathologies
  • Data Interpretation and Assessment: Skill in interpreting data related to medical products and AI model performance.
  • Problem Solving: Ability to identify challenges and recommend solutions.
  • Adaptability: Ability to adapt to varying image resolutions and file formats.

This role offers a unique opportunity to contribute to the development of AI tools that can improve eye health and patient care on a wider scale.
Saviance logo

About Saviance

Sourced by ZipRecruiter

Saviance is a modern consulting firm providing a variety of professional services to its clients in the US. We bring twenty three years of experience to the table. Our consultants are qualified experts and extremely talented. We understand the business behind the technology, and work with many of the top Fortune 100 companies and provide innovative, scalable, robust and secure solutions. At the forefront of the Staffing and IT Solutions industry, Saviance is certified by NMSDC as a Tier 1, Minority Business Enterprise (MBE) . We are a self- certified Small Business and self- certified Woman Owned Business committed to maximizing global workforce solutions on behalf of our clients, empowering businesses and talent through applied human intelligence. We are a Diversity Supplier with global reach specializing in a business services blend of talent, technology, and a relentless commitment to customer success. It’s our diversity that’s acts as a core component of our culture, our approach to business, and the opportunities we provide to our clients and our employees.

Industry

It services

Company size

201 - 500 Employees

Headquarters location

East Rutherford, NJ, US

Year founded

1999

Social media

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