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Data Annotation Project Manager Jobs in Boston, MA

IPG Photonics

Project Manager

Marlborough, MA · On-site

Job Summary The Project Manager leads cross-functional business-improvement projects for the Global ... Experience with PLM and ERP systems, including master data management, BOM structures, and part ...

IPG Photonics

Project Manager

Marlborough, MA · On-site

Job Summary The Project Manager leads cross-functional business-improvement projects for the Global ... Experience with PLM and ERP systems, including master data management, BOM structures, and part ...

FirstLight

Project Manager

Somerville, MA · On-site

$60K - $70K/yr

This role requires strong project leadership, exceptional organizational skills, and the ability to manage diverse service implementations including dark fiber, lit fiber, voice, and data center ...

Analogdevices

Project Manager

Wilmington, MA · Hybrid

The Position The Data Center and Energy Division is seeking an experienced Project Manager to lead teams working on the development of new solutions for the Energy Conversion, Energy Management ...

Analog Devices

Project Manager

Wilmington, MA · On-site

The Position The Data Center and Energy Division is seeking an experienced Project Manager to lead teams working on the development of new solutions for the Energy Conversion, Energy Management ...

Sereact GmbH

Teleoperation Trainer

Boston, MA · On-site

... data collection standards, and act as the critical bridge between project management and the ... Background in data annotation, quality assurance, or structured data collection pipelines

JLL

Senior Project Manager - Data Center

Boston, MA · On-site

Senior Project Manager - Data Centers What this job involves: Lead the end-to-end delivery of the program's most complex, highest-value, and highest-profile mission-critical and data-center ...

Sereact GmbH

Teleoperation Engineer

Boston, MA · On-site

$60K - $90K/yr

... data collection standards, and act as the critical bridge between project management and the ... Background in data annotation, quality assurance, or structured data collection pipelines

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Data Annotation Project Manager information

See Boston, MA salary details

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How much do data annotation project manager jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for data annotation project manager in Boston, MA is $62.48, according to ZipRecruiter salary data. Most workers in this role earn between $54.04 and $73.12 per hour, depending on experience, location, and employer.

What is a data annotation project manager?

A Data Annotation Project Manager is responsible for overseeing projects that involve labeling and categorizing data, such as images, text, or audio, to train machine learning models. They coordinate teams of annotators, manage project timelines, and ensure the quality and accuracy of the annotated data. This role often acts as a bridge between data scientists, clients, and annotation teams, ensuring project requirements are met efficiently and effectively.

What are the key skills and qualifications needed to thrive as a data annotation project manager?

To thrive as a Data Annotation Project Manager, you need strong project management skills, a solid understanding of data annotation processes, and experience with quality assurance, often supported by a degree in a relevant field. Familiarity with annotation tools (like Labelbox or Supervisely), workflow management platforms, and sometimes agile or PMP certification is highly beneficial. Exceptional communication, attention to detail, and leadership abilities help you effectively coordinate teams and ensure project deliverables meet quality standards. These skills are essential for managing complex annotation projects efficiently, maintaining data integrity, and supporting successful machine learning outcomes.

What are some common challenges faced by data annotation project managers, and how can they be managed effectively?

One of the primary challenges Data Annotation Project Managers face is ensuring high-quality, consistent labeling across large and sometimes distributed annotation teams. Managing tight deadlines while maintaining annotation accuracy requires effective training, clear guidelines, and regular quality checks. Additionally, balancing communication between data scientists, clients, and annotators is crucial to align expectations and resolve ambiguities quickly. Successful managers often implement robust feedback loops, leverage annotation tools with built-in quality control features, and foster an open environment for continuous improvement.

What is the difference between Data Annotation Project Manager vs Data Labeling Specialist?

AspectData Annotation Project ManagerData Labeling Specialist
CredentialsTypically requires project management experience, certifications in data management or related fieldsOften requires basic technical skills, familiarity with labeling tools, sometimes certifications in data annotation
Work EnvironmentOversees teams, manages projects, coordinates workflows in office or remote settingsPerforms labeling tasks, often in a remote or on-site environment, focused on data tagging
Employer & Industry UsageUsed by tech companies, AI firms, and data service providers for managing annotation projectsEmployed within similar industries, focusing on executing labeling tasks under supervision

The main difference is that the Data Annotation Project Manager oversees and coordinates annotation projects, ensuring quality and deadlines, while the Data Labeling Specialist focuses on executing the labeling tasks themselves. Both roles are essential in the data annotation process but differ in responsibilities and scope.

What are popular job titles related to Data Annotation Project Manager jobs in Boston, MA?

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Data Annotation Project Manager jobs near you

AI Software Engineer Expert - Remote

YO AI Labs

Boston, MA • Remote

$100 - $200/hr

Part-time

Posted 22 days ago

Job description

Job Title: AI Software Engineering Domain Remote

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Software Engineering Domain Experts to contribute their technical expertise to an innovative project focused on improving next-generation AI systems. In this role, you will evaluate, review, and refine AI-generated software engineering content to enhance the quality, accuracy, and reasoning of AI models. No prior AI experience is required—your software engineering expertise is what matters most.

Key Responsibilities
  • Analyze, review, and improve AI-generated software engineering content for technical accuracy and clarity.
  • Create, refine, and evaluate prompts to improve AI-generated technical outputs.
  • Conduct rubric-based evaluations of AI model responses, providing detailed quality feedback.
  • Draft and edit technical documentation, architecture documents, RFCs, design specifications, and engineering proposals.
  • Perform independent research and fact-checking to validate technical information.
  • Interpret and annotate technical data to support AI model training and evaluation.
  • Collaborate remotely with cross-functional teams to deliver high-quality project outcomes.
Required Skills
  • Critical Thinking
  • Analytical Reasoning
  • Quality Assurance
  • Prompt Engineering
  • AI Output Evaluation
  • Technical Documentation
  • Technical & Professional Writing
  • Content Review & Editing
  • Data Annotation
  • Fact Checking
  • Independent Research
  • Business Communication
  • Problem-Solving
  • Attention to Detail
Preferred Qualifications
  • 3+ years of professional experience as a Software Engineer, Senior Software Engineer, Staff Engineer, Technical Lead, Engineering Manager, Solutions Architect, or similar role.
  • Experience authoring or reviewing technical documentation, architecture documents, RFCs, design specifications, engineering proposals, postmortems, technical blogs, or code reviews.
  • Strong critical thinking, analytical reasoning, and structured problem-solving skills.
  • Excellent written communication and technical editing abilities.
  • Experience with AI coding tools or automated documentation tools is a plus but not required.
  • Advanced degree (Master's, MBA, JD, or PhD) or equivalent professional experience is preferred.