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Data Labeler Remote Jobs in Crofton, MD (NOW HIRING)

HiddenLayer

Data Scientist

Washington, DC · Remote

Data Scientist Remote [within the US] ABOUT THE ROLE: We're looking for a Data Scientist to join ... Security problems rarely come with clean labels or clean data. You're able to frame problems, scope ...

10a Labs

Junior Cyber Investigator

Washington, DC · Remote

$80K - $105K/yr

Review and label AI-generated exchanges to assess whether content provides meaningful offensive ... data extraction, ransomware, local and remote exploits, or offensive security operations

10a Labs

Senior Cyber Investigator

Washington, DC · Remote

$114K - $140K/yr

Review and label AI-generated exchanges, and support label quality across the team to help tune ... data extraction, ransomware, local and remote exploits, or offensive security operations * Strong ...

10a Labs

Principal Cyber Investigator

Washington, DC · On-site +1

$150K - $180K/yr

Oversee day-to-day operations of the embedded team, ensuring exchange labeling and review are ... data extraction, ransomware, local and remote exploits, or offensive security operations

System One

Purview Administrator

Greenbelt, MD · Remote

Remote, with optional onsite work in Washington, DC for local candidates Employment Type: Contract ... labeling, retention, and data loss prevention policies. • Set up and maintain user accounts, role ...

New

System One

Purview Administrator

Greenbelt, MD · Remote

Remote, with optional onsite work in Washington, DC for local candidates Employment Type: Contract ... labeling, retention, and data loss prevention policies. • Set up and maintain user accounts, role ...

New

System One

Purview Administrator

Greenbelt, MD · Remote

Remote, with optional onsite work in Washington, DC for local candidates Employment Type: Contract ... labeling, retention, and data loss prevention policies. • Set up and maintain user accounts, role ...

New

System One

Purview Administrator

Greenbelt, MD · Remote

Remote, with optional onsite work in Washington, DC for local candidates Employment Type: Contract ... labeling, retention, and data loss prevention policies. • Set up and maintain user accounts, role ...

New

System One

Purview Administrator

Greenbelt, MD · Remote

Remote, with optional onsite work in Washington, DC for local candidates Employment Type: Contract ... labeling, retention, and data loss prevention policies. • Set up and maintain user accounts, role ...

New

Astrion

AI Productivity & Power BI Lead

Washington, DC · Remote

$136K - $202K/yr

Remote U.S. JOB STATUS: Full-time CLEARANCE: Secret (Ability to Obtain/Maintain) TRAVEL: As Needed ... You will own data models, agent architectures, refresh schedules, security labels, and the ...

All JobsData Labeler JobsData Labeler Remote JobsData Labeler Remote Jobs in Crofton, MD

Data Labeler Remote information

See Crofton, MD salary details

$15

$39

$57

How much do data labeler remote jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for data labeler remote in Crofton, MD is $39.12, according to ZipRecruiter salary data. Most workers in this role earn between $34.28 and $44.23 per hour, depending on experience, location, and employer.

Is data labelling a good career?

Data labeling is an entry-level role that involves annotating data for machine learning models, often requiring attention to detail and basic technical skills. It can provide a stepping stone into the tech industry, but it typically offers limited advancement opportunities and lower pay compared to more specialized roles. Many professionals use it as initial experience before moving into data science or related fields.

What are the key skills and qualifications needed to thrive as a Data Labeler Remote, and why are they important?

To thrive as a Data Labeler Remote, you need strong attention to detail, basic data analysis skills, and familiarity with data annotation processes, often supported by a high school diploma or equivalent. Proficiency with labeling platforms, annotation tools, and sometimes knowledge of spreadsheet software are typically required. Reliability, time management, and effective communication are crucial soft skills for maintaining accuracy and meeting project deadlines in a remote setting. These skills ensure high-quality, consistent labeled data, which is essential for training reliable machine learning models.

How can I make 2000 a week working from home?

A remote data labeler can potentially earn around $2000 per week by working full-time hours, often 40 hours or more, and gaining experience or specializing in high-demand data annotation tasks. Increasing earnings may involve working for multiple clients, improving skills with annotation tools, or taking on higher-paying projects, but consistent high weekly income depends on workload, rates, and efficiency.

What are some common challenges faced by remote data labelers and how can they be managed?

Remote data labelers often encounter challenges such as maintaining focus during repetitive tasks, ensuring consistent annotation quality, and communicating effectively with distributed teams. To manage these, it's helpful to establish a structured work routine, take regular breaks to prevent fatigue, and use annotation guidelines provided by employers. Leveraging collaboration tools for feedback and clarification also helps maintain high-quality output and fosters a sense of connection with team members.

What does a remote data labeler do?

A remote data labeler is responsible for annotating or tagging data—such as images, videos, audio, or text—from a remote location, typically working from home. Their work helps train machine learning models by providing accurate, labeled datasets that algorithms use to learn and make predictions. Data labelers follow specific guidelines to ensure consistency and accuracy, and may use specialized software tools to complete their tasks. This role is essential in industries like artificial intelligence, self-driving cars, and natural language processing. Remote data labelers often work as freelancers or as part of distributed teams for tech companies.

What is the difference between Data Labeler Remote vs Data Annotator Remote?

AspectData Labeler RemoteData Annotator Remote
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageCommon in AI/ML data preparationCommon in AI/ML data preparation
Job FocusLabeling data points for machine learningAnnotating data for training AI models

Both Data Labeler Remote and Data Annotator Remote roles involve preparing data for AI and machine learning projects. While the terms are often used interchangeably, Data Labeler Remote typically emphasizes labeling data points, whereas Data Annotator Remote may include more detailed annotation tasks. Both roles require similar skills and are performed remotely, making them accessible for individuals seeking flexible data-related jobs.

How much are data labelers paid?

Data labelers working remotely typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the company. Some positions may offer project-based pay or bonuses for accuracy and efficiency.

Is data labeling work from home?

Data labelers often work remotely, as the job typically involves reviewing and annotating data using a computer and internet connection. Many companies offer remote data labeling positions with flexible schedules, requiring basic computer skills and attention to detail.
What job categories do people searching Data Labeler Remote jobs in Crofton, MD look for? The top searched job categories for Data Labeler Remote jobs in Crofton, MD are:
What cities near Crofton, MD are hiring for Data Labeler Remote jobs? Cities near Crofton, MD with the most Data Labeler Remote job openings:
Data Labeler Remote jobs near you
Data Scientist

Data Scientist

HiddenLayer

Washington, DC • Remote

Full-time

Medical, Dental, Vision, Retirement

Re-posted 15 days ago

Job description

Data Scientist

Remote [within the US]

ABOUT THE ROLE:

We're looking for a Data Scientist to join our Data Sciences and ML Engineering team. You'll be building, shipping, and improving the models and LLM-powered systems that sit at the core of our security products — the pieces that make the difference between a tool that flags noise and one that helps defenders find what matters.

This is a hands-on role on a small, focused team. You'll have real ownership over the models and pipelines you build, close collaboration with engineering and product, and the runway to go deep on the hard problems.

WHO WE ARE:

HiddenLayer protects the world's most valuable technologies from adversarial AI attacks. We were founded by AI professionals and security specialists with first-hand experience of how insidious adversarial AI attacks can be to detect and defend against. Determined to prove that these attacks were preventable, the team developed a unique, patent-pending, productized solution to support organizations in accelerating their adoption of AI securely.

Our dedication to innovation has been recognized by prestigious awards such as RSA's Innovation Sandbox Winner, CB Insights AI 100, CyberTech 100, and SC's Most Promising Early-Stage Start-up.

WHAT YOU'LL DO:

Security is a domain where the adversary is adaptive, the signal is rare, and the cost of a miss is real. That makes for interesting modeling problems — ones where off-the-shelf approaches rarely carry you the whole way, and where careful research, solid experimentation, and production rigor each matter for our success.

Your work will span a few areas:

  • Model development and research. Building classifiers, detectors, and scoring models on messy, high-stakes security data. Designing experiments, evaluating trade-offs, and iterating on architectures — not just hyperparameters.
  • LLM agent systems. Shaping the prompts, context, tool-use patterns, and supporting content that drive our LLM agents.
  • Production delivery. Shipping models behind real traffic, monitoring them, and improving them over time.
  • Evaluation and iteration. Building the evaluation harnesses and feedback loops that let us know whether a change is actually an improvement — often the hardest part of the work. Our models only improve for customers when our evaluations highlight what really matters.

WHO YOU ARE:

Production experience is the single most important thing. We'd like to see around 3–4+ years of experience delivering models into production environments where they've had to perform, be maintained, and evolve. That's the background that tends to set people up for success here.

Beyond that:

  • Depth in ML fundamentals. You understand model architectures and can reason about why a given approach is or isn't a good fit for a problem. You've moved well past treating models as black boxes and past tuning that stops at sample weights and decision thresholds.
  • Willingness to experiment. You're comfortable trying genuinely novel approaches when the standard playbook runs out, and you can tell the difference between a promising result and a fragile one.
  • Strong engineering instincts. Your code is something teammates can read, extend, and trust in production. You think about reproducibility, testing, and handoff — not just whether something runs on your laptop.
  • Experience with LLMs in practice. You've worked with LLM-based systems in some real capacity — prompting, context design, tool use, evaluation, or fine-tuning — and have opinions shaped by actually shipping things.
  • Comfort with ambiguity. Security problems rarely come with clean labels or clean data. You're able to frame problems, scope them, and make progress without a fully paved path. You'll help highlight ambiguity and reason about how to make progress even when humans don't all agree on one single answer.
  • An advanced degree (MS or PhD) in a technical discipline. This doesn't have to be in data science or ML specifically — strong backgrounds in CS, statistics, physics, math, engineering, and related fields are all welcome. Your on-the-job experience is what matters the most.

We want to be upfront about research and publications: while we're supportive of engagement with the broader research community, our team's focus is firmly on shipping. Publishing papers and attending conferences can absolutely happen, but they aren't the center of gravity of the role. If your primary goal is academic output, this probably isn't the best fit — and we'd rather say that clearly than have it be a surprise.

WHY HIDDENLAYER?

We're moving at (what feels like) the speed of light. HiddenLayer is a venture-backed company and recently closed a $50M funding round led by M12, Microsoft's Venture Fund, and Moore Strategic Ventures.

Attracting and retaining the very best people is our #1 priority. That's why we offer our team best-in-class benefits, including:

  • Fully Remote: We are a completely remote global team. Though we're distributed, we are intentional about getting the team together a couple of times a year. We offer a generous stipend for your home office setup, annual upgrades to ensure you have a comfortable workspace and a monthly stipend for internet/phone expenses.
  • Comprehensive Health & Wellness Benefits: Better than your average startup healthcare benefits. With five options to choose from, of which are fully subsidized by HiddenLayer, we offer a variety of options to fit each person's needs. We also offer vision, dental, and 401k offerings.
  • Flexible Time Off: Enjoy unlimited and flexible time off for all salaried employees, in addition to 15 paid company holidays.
  • Commitment to Learning and Development: We support personal growth and education through a dedicated L&D fund that can be used for training, conferences, certifications and industry events.
  • Diversity, Equity, and Inclusion: We are committed to building a diverse team with individuals from various backgrounds, experiences, abilities, and perspectives, and we are proud to be an equal opportunity employer.

To learn more about HiddenLayer visit HiddenLayer and follow us on LinkedIn or Twitter.

HiddenLayer is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, age, marital status, political affiliation, sexual orientation, gender identity, genetic information, disability or protected veteran status. We are committed to providing a workplace free of any discrimination or harassment.