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Data Annotation Law Jobs in Boston, MA (NOW HIRING)

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Data Annotation Law information

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

To thrive as a Data Annotation Specialist, you need keen attention to detail, strong analytical skills, and a basic understanding of data labeling protocols, often supported by a high school diploma or relevant training. Familiarity with data annotation tools like Labelbox, Supervisely, or CVAT, as well as knowledge of data privacy regulations, is typically required. Excellent communication, time management, and consistency are vital soft skills for collaborating with teams and maintaining annotation quality. These skills ensure accurate, reliable data labeling, which is critical for developing effective machine learning models.

What is the difference between Data Annotation Law vs Data Labeler?

AspectData Annotation LawData Labeler
CredentialsLegal knowledge, compliance certificationsBasic training, attention to detail
Work EnvironmentLegal offices, compliance departmentsData annotation platforms, remote or office settings
Industry UsageLegal, AI compliance, data privacyAI training, machine learning datasets
Search & ComparisonLegal roles, compliance in data annotationData labeling, data annotation jobs

Data Annotation Law involves legal expertise ensuring data annotation processes comply with laws and regulations, often requiring legal certifications. Data Labelers focus on annotating data for AI models, typically with basic training. While both roles work within data annotation, Data Annotation Law emphasizes legal compliance, whereas Data Labelers concentrate on data preparation for machine learning.

What is data annotation law?

Data Annotation Law refers to the legal frameworks and regulations that govern the process of labeling, tagging, or categorizing data for use in machine learning and artificial intelligence applications. These laws address issues such as data privacy, intellectual property, consent, and the ethical use of annotated data. Data Annotation Law ensures that organizations handle data responsibly and comply with national and international standards when using human annotators or automated systems. It is crucial for companies to understand these legal requirements to avoid potential legal liabilities and protect the rights of data subjects.

What are some common challenges faced by professionals working in data annotation for the legal industry, and how can they be addressed?

Professionals in data annotation law often encounter challenges such as interpreting complex legal language, ensuring consistency and accuracy in labeling, and maintaining confidentiality with sensitive information. Collaboration with legal experts and ongoing training in legal terminology are essential to address these issues. Additionally, many organizations implement rigorous quality assurance processes and utilize annotation guidelines to help annotators navigate ambiguous cases and improve overall data quality.

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

For Data Annotation Law jobs in Boston, MA, the most frequently searched job titles are:

What job categories do people searching Data Annotation Law jobs in Boston, MA look for?

The top searched job categories for Data Annotation Law jobs in Boston, MA are:

What cities near Boston, MA are hiring for Data Annotation Law jobs?

Cities near Boston, MA with the most Data Annotation Law job openings:

Data Annotation Law jobs near you
Infographic showing various Data Annotation Law job openings in Boston, MA as of August 2026, with employment types broken down into 83% Full Time, 12% Part Time, and 5% Contract. Highlights an 78% In-person, 7% Hybrid, and 15% Remote job distribution.

Project Perseus \u007C Data Labeling Associate -Turkish Speakers (Human-in-the-Loop AI)

Welo Data

Boston, MA • On-site

$34/hr

Full-time

Re-posted 19 days ago

Job description

Overview

Welo Data is looking for sharp, curious, and detail-oriented individuals to join our team as Data Labeling Associate.

This is not a traditional annotation role.

You’ll be working directly with cutting-edge AI systems — evaluating outputs, identifying gaps, and helping improve how these systems behave in real-world scenarios. The work sits at the intersection of data quality, model evaluation, and human judgment, where your ability to think critically matters just as much as following guidelines.

We’re looking for people who are naturally curious about AI, comfortable forming opinions, and confident in contributing to conversations with teammates, leads, and stakeholders.

Project Details

  • Job Title: Data Labeling Associate
  • Hiring in: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston
  • Hours: Full-time, 40 hours per week
  • Employment Type: W2 Full-Time Employee
  • Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship)
  • Pay Rate: $34/hour
  • Contract Duration: 1-year contract with possibility of extension
Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: New York City, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston. Please only apply if you meet this location requirement.
What You’ll Do
  • Evaluate AI model outputs and provide structured, high-quality feedback
  • Perform audit-based reviews of data and model behavior — identifying patterns, edge cases, and failure modes
  • Apply guidelines thoughtfully — and flag when they don’t reflect real-world scenarios
  • Contribute to improving evaluation frameworks, not just executing them
  • Identify trends in model performance and communicate insights clearly
  • Participate in team discussions, calibrations, and stakeholder syncs
  • Partner with leads and cross-functional teams to refine quality standards
  • Document findings in a clear, concise, and actionable way
What We’re Looking For
  • Native-level language proficiency and a university degree (Bachelor’s or higher).
  • B2 or superior level of English.  
  • 1–2 years of professional writing experience with strong, structured writing skills
  • Ability to apply complex writing rules and guidelines consistently
  • Strong understanding of safety considerations in GenAI data delivery, with 2+ years of relevant experience
  • Strong critical thinking and attention to detail
  • Ability to make sound judgment calls in ambiguous situations
  • Naturally curious about AI, technology, and how systems behave
  • Comfortable speaking up, asking questions, and contributing ideas
  • Strong written and verbal communication skills
  • Ability to stay consistent while working with evolving guidelines
  • Experience in data quality, QA, annotation, or analysis is helpful — but not required
Benefits
  • Paid Vacation: 6 days
  • Paid Company Holidays: 2 days (Memorial Day and Labor Day)
  • Paid Sick Leave: accrued per applicable state law and company policy
  • Medical, Dental, and Vision Insurance (eligibility applies)
  • Health Savings Account (HSA)
  • 401(k) Retirement Plan
  • Employee Assistance Program
  • Additional voluntary benefits (life, accident, critical illness, etc.)
  • Free Gourmet Food: Free breakfast, lunch, and dinner are provided, featuring a wide variety of cuisines in multiple cafes.
  • Micro-kitchens & Snacks: Offices are stocked with free snacks and beverages, including premium coffee and La Croix.
  • Unique Campus Features: Some locations include roof-top nature parks
  • Commuter Benefits: Free transport, shuttles, and sometimes bike-to-work perks.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.