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

Hatch IT

NLP/Linguistics Software Engineer

Somerville, MA · On-site

$125K - $150K/yr

About the Company Babel Street is the trusted technology partner for the world's most advanced ... Experience with data quality evaluation, data annotation, or guideline design, preferably for ...

Hatch IT

NLP/Linguistics Software Engineer

Somerville, MA · On-site

$125K - $150K/yr

About the Company Babel Street is the trusted technology partner for the world's most advanced ... Experience with data quality evaluation, data annotation, or guideline design, preferably for ...

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Data Annotation Tech information

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How much do data annotation tech jobs pay per hour?

As of Aug 17, 2026, the average hourly pay for data annotation tech in Boston, MA is $24.82, according to ZipRecruiter salary data. Most workers in this role earn between $18.27 and $29.52 per hour, depending on experience, location, and employer.

What is a data annotation tech?

A Data Annotation Tech is responsible for labeling and categorizing data, such as text, images, audio, or video, to train machine learning models. They follow specific guidelines to ensure accuracy and consistency in annotations, which helps improve the performance of AI systems. This role often involves repetitive tasks, attention to detail, and familiarity with various annotation tools. Data annotation is crucial for AI development in industries like healthcare, finance, and autonomous driving.

What does a data annotation tech do?

A typical day as a Data Annotation Tech involves reviewing large sets of data—such as images, text, or audio—and accurately labeling or categorizing them using specialized software. You may work independently or as part of a team, following specific project guidelines to ensure data integrity and consistency. Collaboration with project managers or data scientists is common when clarifying ambiguous data points or addressing annotation challenges. Additionally, productivity targets and quality checks are a regular part of the workflow, helping to keep projects on schedule and maintain high standards.

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

To thrive as a Data Annotation Tech, you need keen attention to detail, basic computer literacy, and familiarity with data labeling standards, often supported by a high school diploma or equivalent. Experience with annotation platforms, image or text labeling tools, and basic knowledge of data management systems is highly valuable. Strong organizational skills, patience, and effective communication set top candidates apart in this field. These skills and qualities ensure annotated data is accurate, consistent, and valuable for machine learning or AI projects.

Does data annotation actually pay you?

Data annotation jobs typically pay hourly or per task, with rates varying depending on the platform and complexity of the work. Many companies and platforms offer remote opportunities that provide consistent payment once tasks are completed, often requiring basic skills in data labeling tools. Payment is generally reliable for those who meet quality standards and adhere to deadlines.

How much do data annotation technicians make?

Data annotation technicians typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the tasks. Many roles are entry-level and may offer flexible schedules or remote work opportunities.

How to become a data annotation tech?

To become a data annotation tech, you typically need a high school diploma or equivalent, strong attention to detail, and familiarity with data labeling tools or software. Some roles may require basic knowledge of machine learning concepts or specific platforms like Labelbox or CVAT. Gaining experience through online courses or tutorials can also improve job prospects.

What are the most commonly searched types of Data Annotation Tech jobs in Boston, MA?

The most popular types of Data Annotation Tech jobs in Boston, MA are:

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

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

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

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

Data Annotation Tech jobs near you
Infographic showing various Data Annotation Tech 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, with an average salary of $51,617 per year, or $24.8 per hour.

NLP/Linguistics Software Engineer

Hatch IT

Somerville, MA • On-site

$125K - $150K/yr

Full-time

Re-posted 25 days ago

Job description

hatch I.T. is partnering with Babel Street to find an NLP/Linguistics Software Engineer. Please see details below:

About the Role

Babel Street is looking for a Software Engineer to join their Analytics Group. This is an execution-focused "builder" role for an engineer early in their career who wants to work at the intersection of NLP algorithms, search engines, and data science techniques. In this role, you will help create the next generation of architecture and components for their analytics platform, focusing specifically on their record matching functionality. You will bridge the gap between linguistic theory and practical AI applications, helping us implement practical, innovative text analytics and AI-driven features. You will work closely with senior engineers to learn how to deliver software that is safe, reliable, and production-ready.

About the Company

Babel Street is the trusted technology partner for the world's most advanced identity intelligence and risk operations. They deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360-degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empowers government and commercial organizations to transform high-stakes identity and risk operations into a strategic advantage.  The actionable insights we deliver safeguard lives and protect critical assets around the world.  Babel Street is headquartered in Reston, Virginia, with regional offices in Boston, MA and Cleveland, OH, and international offices in Australia, Canada, Israel, Japan, and the U.K.

What you will do:
  • Implement and Maintain: Write high-quality, maintainable code to support the analytics platform and its record matching components.
  • Bridge Theory and Practice: Take theoretical ideas from linguistics and data science and implement them as practical software features.
  • Support Search Internals: Help optimize and maintain search engine components, including Elasticsearch data modeling and performance tuning.
  • Collaborate and Learn: Participate in agile sprint planning and work daily with senior partners to translate project requirements into technical solutions.
  • Build Scalable Systems: Assist in designing and shipping robust APIs and scalable architectures that integrate into our AI-native platform.
What you will bring:

Required:

  • 2-4 years of professional software engineering experience (including high-impact internships or projects).
  • Proficiency in Java (our core analytics language) or Python (for AI/ML integrations).
  • Problem Solver: Ability to work across teams and make steady progress in ambiguous problem spaces.
  • Educational Foundation: Bachelor's degree in Computer Science, Linguistics, or a related technical field.

Preferred (Nice to Have):

  • Foundation in Data Science: Experience with data quality evaluation, data annotation, or guideline design, preferably for linguistics.
  • Familiarity with Elasticsearch internals or other search/retrieval-based systems.
  • Exposure to computational linguistics or natural language processing (NLP).
  • Interest in Kubernetes and cloud-native architectures.
What success looks like:
  • Month 1-2: Ramp up on the analytics stack and record matching architecture; ship your first initial changes to production.
  • Month 3-4: Take ownership of a specific component or pipeline improvement with guidance, including full testing and documentation.
  • Month 5-6: Deliver a measurable improvement to record matching quality or pipeline reliability and contribute to team design discussions.
Why this role matters:
The record matching functionality is where Babel Street's signals become usable intelligence. Do you care about provenance, explainability, and trust? When a match decision affects whether someone is onboarded or investigated, "the model said so" is not good enough. You will help build systems where every match is defensible, auditable, and tunable - a rare luxury in modern ML-heavy stacks. Do you speak multiple languages? Since our platform processes data from around the globe, your linguistic insights can directly inform how we build and polish the NLP and computational linguistics components that make our record matching world-class.
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.
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