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Data Annotation information

What does a typical workday look like for someone in a Data Annotation role?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

Is data annotation a genuine job?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It often requires attention to detail and familiarity with annotation tools, and can be found in various industries like technology and healthcare.

Does data annotation pay well?

Data annotation jobs typically offer entry-level pay that varies depending on the employer, location, and complexity of the tasks. While some positions pay hourly wages comparable to other administrative or clerical roles, experienced annotators working on specialized projects or with advanced tools can earn higher rates. Overall, data annotation is often considered an entry-level position with moderate pay potential.

What is a Data Annotation job?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

How hard is it to get hired by data annotation?

Getting hired for a data annotation role generally requires basic computer skills, attention to detail, and sometimes familiarity with specific tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible, though competition can vary based on the employer and location.

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

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What does a data annotator do?

A data annotator labels and tags data such as images, text, or videos to help machine learning models understand and learn from the data. They use tools and follow guidelines to ensure accuracy and consistency, often working with large datasets in a structured environment. Attention to detail and knowledge of annotation tools are important for this role.
What are the most commonly searched types of Data Annotation jobs in Chelsea, MA? The most popular types of Data Annotation jobs in Chelsea, MA are:
What job categories do people searching Data Annotation jobs in Chelsea, MA look for? The top searched job categories for Data Annotation jobs in Chelsea, MA are:
What cities near Chelsea, MA are hiring for Data Annotation jobs? Cities near Chelsea, MA with the most Data Annotation job openings:
Data Annotation jobs near you
Infographic showing various Data Annotation job openings in Chelsea, MA as of July 2026, with employment types broken down into 2% Locum Tenens, 33% Full Time, 26% Part Time, 2% Contract, 36% Nights, and 1% Summer. Highlights an 55% Physical, 2% Hybrid, and 43% Remote job distribution.
NLP/Linguistics Software Engineer

NLP/Linguistics Software Engineer

Babel Street

Somerville, MA

$125K - $150K/yr

Other

Medical, Dental, Vision, Life, Retirement

Posted 6 days ago

Job description

ROLE SUMMARY

Babel Street is looking for a Software Engineer to join our 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 our analytics platform, focusing specifically on our 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.

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.

WHAT YOU'LL DO (KEY RESPONSIBILITIES)

  • 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 BRING (QUALIFICATIONS)

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 (FIRST SIX MONTHS)

  • 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.

Benefits at Babel Street (just to name a few...)

  • Health Benefits: Babel Street covers 85-100% monthly premium costs for Medical, Dental, Vision, Life & Disability insurances - for you and your family!
  • Retirement Plans: Babel Street offers both a Traditional and Roth 401(K) with a very competitive match.
  • Unlimited Flexible Leave: We trust our employees to manage their own time and balance their personal and work lives.
  • Holidays: Babel Street provides employees with 12 paid Federal Holidays
  • Tuition Reimbursement: We are committed to investing in our employees. One way we do that is with our Tuition Reimbursement Program for continuing education.                 

Babel Street is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. Further, Babel Street will not discriminate against applicants for inquiring about, discussing or disclosing their pay or, in certain circumstances, the pay of their coworker, Pay Transparency Nondiscrimination. In addition, Babel Street's policy is to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works. Upon request, we will provide you with more information about such accommodations.

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