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Data Annotation For Ai Jobs in Boston, MA (NOW HIRING)

About the Role Field AI is transforming how robots interact with the real world. Our R&D team, the ... Write and maintain QA scripts for in-house and vendor data drops. * Build and maintain annotation ...

Write and maintain QA scripts for in-house and vendor data drops. * Build and maintain annotation ... Why Join Field AI? FieldAI is tackling one of robotics' hardest problems: deploying robots in ...

About the Role Field AI is transforming how robots interact with the real world. Our R&D team, the ... Write and maintain QA scripts for in-house and vendor data drops. * Build and maintain annotation ...

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

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Data Annotation For Ai information

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.
What job categories do people searching Data Annotation For Ai jobs in Boston, MA look for? The top searched job categories for Data Annotation For Ai jobs in Boston, MA are:
What cities near Boston, MA are hiring for Data Annotation For Ai jobs? Cities near Boston, MA with the most Data Annotation For Ai job openings:
Infographic showing various Data Annotation For Ai job openings in Boston, MA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, and 5% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Ophthalmologist (Medical Data Labeling Specialist)

Saviance

Boston, MA • On-site

Other

Re-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

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