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

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How much do remote data labeling jobs pay per hour?

As of May 31, 2026, the average hourly pay for remote data labeling in Silver Spring, MD is $35.12, according to ZipRecruiter salary data. Most workers in this role earn between $17.45 and $47.45 per hour, depending on experience, location, and employer.

What is a Remote Data Labeling job?

A Remote Data Labeling job involves annotating or categorizing data, such as images, text, audio, or video, to train machine learning models. Workers review and tag content based on specific guidelines provided by companies. This job is typically done online from home and requires attention to detail, consistency, and sometimes specialized domain knowledge. It plays a crucial role in improving artificial intelligence systems by providing high-quality labeled data.

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

To thrive as a Remote Data Labeling specialist, you need strong attention to detail, basic data analysis skills, and the ability to accurately tag and categorize diverse data types, often with a high school diploma or equivalent. Familiarity with data labeling platforms, annotation tools (such as Labelbox or Amazon SageMaker Ground Truth), and, occasionally, basic knowledge of data privacy standards is helpful. Time management, self-discipline, and effective remote communication are valuable soft skills in this position. These skills ensure that labeled data is accurate and reliable, supporting the success of machine learning and AI projects.

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

Remote data labelers often face challenges such as maintaining focus during repetitive tasks, managing volume-based workloads, and interpreting ambiguous data with consistency. To manage these, it's important to set up a distraction-free workspace, take regular breaks to avoid fatigue, and seek clarification from supervisors or project guidelines when uncertainties arise. Most companies provide onboarding and ongoing support to help new labelers understand annotation standards and best practices. Collaborating with remote team members via chat or project management platforms also helps maintain quality and stay connected. By being proactive and utilizing available resources, remote data labelers can maintain high accuracy and productivity.
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Remote Data Labeling jobs near you
Infographic showing various Remote Data Labeling job openings in Silver Spring, MD as of May 2026, with employment types broken down into 50% Full Time, 36% Part Time, 7% Temporary, and 7% Contract. Highlights an 100% Remote job distribution, with an average salary of $73,060 per year, or $35.1 per hour.

AWS Cloud Solutions Architect (GovCloud) Remote

Private Label Staff

Baltimore, MD • Remote

$57 - $76.25/hr

Full-time

Posted 24 days ago

Job description

Salary:

Overview

We are seeking a Mid-Level AWS Cloud Engineer / Systems Administrator to support the design, implementation, and maintenance of a secure, scalable AWS GovCloud environment. This role will play a key part in cloud migration initiatives, ongoing operations, and ensuring compliance with federal security standards.


This is aremote position supporting a federal environment. Candidates must be eligible to obtain a Public Trust clearance.


Key Responsibilities

  • Design, implement, and maintain secure, scalable AWS cloud environments
  • Translate business and technical requirements into effective cloud architecture solutions
  • Support cloud migration efforts, including planning, data transfer, and workload refactoring
  • Manage and optimize AWS services (EC2, S3, RDS, IAM, VPC, CloudFormation)
  • Monitor system performance, ensuring high availability and reliability (targeting 99.999% uptime)
  • Implement security controls, compliance frameworks, and monitoring solutions
  • Collaborate with developers and data engineers to integrate applications and cloud services
  • Automate infrastructure and processes using scripting and Infrastructure as Code (IaC)
  • Maintain technical documentation, architecture diagrams, and operational procedures
  • Perform system patching, upgrades, and continuous monitoring
  • Support disaster recovery planning, testing, and execution
  • Contribute to Agile development cycles, including planning, troubleshooting, and deployment


Required Qualifications

  • Ability to obtain and maintain a Public Trust clearance
  • 2+ years of experience in cloud engineering, systems administration, or cloud architecture
  • Hands-on experience with AWS GovCloud and core AWS services (EC2, S3, RDS, IAM, VPC, CloudFormation, CloudWatch)
  • Strong understanding of cloud security principles and compliance frameworks
  • Experience with cloud migration and hybrid/multi-cloud environments
  • Familiarity with containerization and orchestration (Docker, Kubernetes, ECS, or EKS)
  • Proficiency in scripting or automation (Python, Bash, or similar)
  • Strong problem-solving, communication, and collaboration skills


Preferred Qualifications

  • AWS Certified Solutions Architect (Associate or Professional)
  • Experience with Infrastructure as Code tools (Terraform, Ansible, etc.)
  • Familiarity with AWS data and analytics tools (Redshift, Athena, etc.)
  • Experience supporting federal government or law enforcement environments
  • Experience deploying and managing containerized applications in Kubernetes
  • Hands-on experience with Amazon EKS and cloud-native application modernization


Environment & Scope

  • Support AWS-hosted infrastructure for a federal agency environment
  • Participate in a multi-year cloud migration and modernization initiative
  • Provide operations, maintenance, and monitoring of production systems
  • Ensure compliance, auditing, and reporting requirements are met
  • Deliver documentation and knowledge transfer to internal stakeholders


What Success Looks Like

  • Successful migration of critical workloads to AWS
  • Highly available, secure, and optimized cloud environment
  • Strong documentation, monitoring, and disaster recovery processes in place
  • Seamless collaboration across engineering, data, and security teams