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

Shift work will be required, and rotating shift work will be necessary. • Participates in other testing of new algorithm outputs and capabilities, to include data labeling in support of maritime ...

JBlocks Software Engineer

Hanover, MD · On-site

$94K - $198K/yr

Develop and enhance software capabilities that meet evolving data labeling and marking requirements. Work closely with team developers to design, implement, and test new features. Contribute ...

This role serves as a trusted advisor to government and industry partners, providing expertise in AI/ML data labeling, imagery exploitation tradecraft, and computer vision initiatives across the full ...

Leads labelling updates and development, critically evaluating the data and principles upon which labelling statements are based to ensure clinical relevance and regulatory acceptance across the ...

Machine Learning Engineer- Senior

Chantilly, VA · On-site

$125K - $165K/yr

Understanding of how to craft prompts for discrete tasks such as data labeling and processing. * Experience with asynchronous Python development using frameworks like Ray and FastAPI. * Experience ...

Machine Learning Engineer- Senior

Chantilly, VA · On-site

$125K - $165K/yr

Understanding of how to craft prompts for discrete tasks such as data labeling and processing. * Experience with asynchronous Python development using frameworks like Ray and FastAPI. * Experience ...

Showing results 41-60

Data Labeling information

See Silver Spring, MD salary details

$10

$25

$59

How much do data labeling jobs pay per hour?

As of Sep 8, 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 data labeling?

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 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.

What are the key skills and qualifications needed to thrive in data labeling, 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.

How can I get started in data labeling?

To get started in data labeling, you should develop basic skills in data annotation tools and understand labeling guidelines for different data types such as images, text, or audio. Many entry-level positions require attention to detail and sometimes a background in relevant fields like computer science or linguistics; online courses and practice datasets can help build your skills. Additionally, creating a strong profile on job platforms and applying to companies that offer remote or flexible data labeling roles can increase your chances of starting in this field.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform or employer. Some may work as freelancers or part-time, with pay rates varying accordingly.

Is data labeling a good career?

Data labeling is a growing field that involves annotating data for machine learning models, often requiring attention to detail and familiarity with tools like labeling platforms. It can offer flexible schedules and entry-level opportunities, but typically provides lower pay compared to other tech roles and may lack long-term career advancement without additional skills. Overall, it can be a suitable starting point for those interested in AI and data science, but may not be ideal as a long-term career without further development.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help train machine learning models. These roles typically require attention to detail and familiarity with labeling tools or software, and may be performed remotely or in a team environment.

What are popular job titles related to Data Labeling jobs in Silver Spring, MD?

For Data Labeling jobs in Silver Spring, MD, the most frequently searched job titles are:

What cities near Silver Spring, MD are hiring for Data Labeling jobs?

Cities near Silver Spring, MD with the most Data Labeling job openings:

Infographic showing various Data Labeling job openings in Silver Spring, MD as of August 2026, with employment types broken down into 75% Full Time, 6% Part Time, 7% Temporary, and 12% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $52,137 per year, or $25.1 per hour.

Strategic Projects Lead, Public Sector - Cyber Washington, DC Apply →

Washington, DC • On-site

Scale AI, Inc.
Software Development • 201 - 500 employees

$150 - $200/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago


Scale AI rating

8.5

Company rating: 8.5 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

82nd of 247 rated software companies


Job description

Scale AI is at the frontier of the AI industry, improving the world’s leading generative AI and large language models through model evaluations, human-powered supervised fine-tuning datasets, world-class reinforcement learning with human feedback, and more.

Scale AI’s Public Sector team is growing in the Generative AI, Public Sector space, and we’re seeking a Cyber focused Strategic Projects Lead to lead high-impact cyber projects that drive experimentation. In this role, you’ll work across operations, engineering, customer engagement, and directly with our clients to produce world-class cyber test and evaluation and training data for Large Language Models for our Public Sector customers.

This role offers a rare opportunity to make a meaningful impact at the intersection of cyber, AI and national security. You will build human data labeling pipelines from the ground up, create operational processes to manage and optimize an in-house expert data workforce, and develop novel technology-driven approaches (e.g., scripts, prompt engineering, hybrid data) to improve the quality of both our training and evaluation datasets. You will also own the financial and technical viability of your programs by managing project COGS and partnering with Go-to-Market teams to scope customer engagements through taxonomy design and feasibility validation, ensuring deals are scalable, executable, and economically sound. In addition, you will partner directly with our internal machine learning experts and external stakeholders to ensure our data enables the development of mission-critical applications of AI.

Help shape the future of AI by joining a fast-growing team built on exceptional data, tools, and systems.

You Will:
  • Develop, build, and maintain the operations infrastructure required to ensure data labeling pipelines are efficient, scalable, and produce high-quality outputs.
  • Partner closely with customers to understand their requirements and design dataset taxonomies that evaluate agents and models or improve model performance.
  • Take ownership of day-to-day progress on high-priority data production pipelines, ensuring projects move forward efficiently
  • Partner with subject matter experts in their fields to validate the quality of our data and to translate deep cyber domain knowledge into scalable processes and measurable outcomes.
  • Work with our Machine Learning and Go-to-Market teams to scope customer engagements via technical feasibility validation to ensure deals are scalable and executable.
  • Influence cross-org collaboration to define and advance human data strategy, influencing technical and non-technical stakeholders to ensure data quality, scalability, and long-term platform leverage.
  • Own the financial health of programs by managing project-level COGS through workforce planning, tooling decisions, and process optimization.
  • Utilize analytics and data visualization tools to track progress, identify bottlenecks, and make data-driven decisions to optimize pipeline performance
  • Own larger and larger components of our data delivery processes, until you ultimately serve as the full owner of our most visible and high impact customer pipelines
You have:
  • An active Top Secret security clearance
  • Demonstrated experience in cybersecurity domains such as penetration testing, red/blue teaming, vulnerability assessment, network security, or cyber operations.
  • 2-3 years of experience in product development, data science, or operations
  • A history of successful project management and comfort in ambiguity
  • Ability to analyze complex operational data, build queries, and identify trends to inform decisions and optimize processes
  • Technical aptitudeto understand how to produce data for state of the art post-training techniques such as supervised fine tuning (SFT), reinforcement learning through human feedback (RLHF), Reinforcement Learning with Verifiable Rewards (RLVR) etc
Nice to have:
  • Experience working in defense tech and/or an AI company
  • A technical degree in fields like computer science, data science, or engineering
  • A deep understanding of ML operations for generative AI workflows / products

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

The base salary range for this full-time position in the location of Washington DC is:

$139,200 — $174,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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