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Data Labeling Jobs in Silver Spring, MD (NOW HIRING)

Peraton

Data Architect, SME

Herndon, VA · On-site

$146K - $234K/yr

Establish secure cross-domain data exchange strategies, data labeling/releasability controls, and defensible data sharing patterns supporting SOC, CIRT, threat intelligence, and vulnerability ...

Peraton

Data Architect, SME

Herndon, VA

$146K - $234K/yr

Establish secure crossdomain data exchange strategies, data labeling/releasability controls, and defensible data sharing patterns supporting SOC, CIRT, threat intelligence, and vulnerability ...

Redhorse Corporation

Data Scientist

Arlington, VA · On-site +1

Data Scientist with 4 years of experience including experience in applied NLP, data labeling, entity or keyword extraction, and related topics. * Understanding of Weibull distribution and use for ...

Steampunk

Data Scientist (Generative AI)

Mclean, VA

$125K - $160K/yr

We are looking for seasoned Data Scientist (Generative) to work with our existing team of Data ... Identify, clean, label, and synthesize high-quality datasets for model training, fine-tuning, or ...

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Data Labeling information

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How much do data labeling jobs pay per hour?

As of May 31, 2026, the average hourly pay for data labeling in Silver Spring, MD is $25.07, according to ZipRecruiter salary data. Most workers in this role earn between $16.47 and $28.76 per hour, depending on experience, location, and employer.

What is a Data Labeling job?

A Data Labeling job involves annotating or tagging data, such as images, text, audio, or videos, to help train machine learning models. Labelers follow specific guidelines to classify data accurately so that AI systems can learn patterns and make predictions. This role is essential in fields like computer vision, natural language processing, and speech recognition. Strong attention to detail and consistency are crucial for ensuring high-quality training datasets.

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

To thrive in Data Labeling, you need meticulous attention to detail, strong analytical abilities, and basic computer literacy, often supported by a high school diploma or equivalent. Familiarity with data annotation tools, image or text editing software, and experience with platforms like Labelbox or Amazon SageMaker Ground Truth are commonly advantageous. Exceptional concentration, patience, and the ability to follow precise instructions are valuable soft skills in this position. These skills and qualities are essential for ensuring the accuracy and consistency of labeled datasets, which are critical for training reliable AI and machine learning models.

What are the typical day-to-day responsibilities of a Data Labeling professional?

A Data Labeling professional is primarily responsible for reviewing and accurately tagging images, text, audio, or video data according to specified guidelines. Daily tasks often include managing large datasets, using annotation software to classify data, and verifying the quality and accuracy of the labels. Collaboration with data scientists, project managers, and other annotators is common, especially when clarifying labeling guidelines or resolving ambiguities. Attention to detail is crucial, as high-quality labeled data directly impacts the effectiveness of machine learning models and AI applications. Most positions are structured in team environments, where productivity and communication skills help ensure project deadlines are met.
More about Data Labeling jobs
What are the most commonly searched types of Data Labeling jobs in Silver Spring, MD? The most popular types of Data Labeling jobs in Silver Spring, MD are:
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Data Labeling jobs near you
Infographic showing various Data Labeling job openings in Silver Spring, MD as of May 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 25% Physical, and 75% Remote job distribution, with an average salary of $52,137 per year, or $25.1 per hour.
Project Perseus \u007C Data Quality Analyst - Hindi Speakers (Human-in-the-Loop AI)

Project Perseus \u007C Data Quality Analyst - Hindi Speakers (Human-in-the-Loop AI)

Welo Data

Washington, DC

$38/hr

Full-time

Posted 4 days ago

Job description

Welo Data is looking for experienced, detail-oriented professionals to join our team as Data Quality Analysts. This role sits at the center of execution and quality — bridging Data Labeling Associates (DLAs) and Team Leads to ensure work is not only completed, but done right.

You'll work closely with both people and AI systems — auditing outputs, supporting day-to-day execution, and helping teams apply guidelines correctly in fast-moving, real-world scenarios. The work combines data quality, light project coordination, and hands-on training, where your ability to guide others and think critically is just as important as your own output.

Project Details

  • Job Title: Data Quality Analyst
  • 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: $38/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: NYC, 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
  • Support quality and execution across DLA teams, ensuring work meets defined standards at scale
  • Audit DLA outputs and provide structured, actionable feedback to improve accuracy and consistency
  • Act as the first line of support for DLAs — answering questions and helping interpret guidelines
  • Help DLAs navigate ambiguity and apply evolving instructions effectively
  • Support onboarding and training of new DLAs through hands-on guidance and coaching
  • Monitor workflows, queues, and blockers — escalating risks and gaps to Team Leads
  • Identify patterns, recurring issues, and edge cases in both human and model outputs
  • Participate in calibrations, team discussions, and stakeholder syncs
  • Contribute to improving guidelines, processes, and overall team performance
  • Document findings and feedback 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.  
  • 2–4 years of experience in data annotation, content quality, QA, or related fields
  • Strong ability to interpret and apply complex guidelines with consistency
  • Excellent attention to detail with a high bar for quality
  • Ability to stay consistent while working with evolving guidelines and priorities
  • Experience in AI/ML data workflows or human-in-the-loop evaluation environments
  • Prior experience auditing or reviewing the work of others
  • Familiarity with safety, compliance, or policy-driven content evaluation
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.
Why This Role

This is an opportunity to move beyond traditional data work and play a direct role in how AI systems are evaluated and improved. The work is fast-moving, collaborative, and increasingly central to how modern AI systems are built and deployed.

Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.
 
To know more details (Click here)
 
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.
 
 
As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
 
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.