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Ai Data Annotation Remote Jobs in Washington (NOW HIRING)

SAIC

AI Data Engineer

Fort Belvoir, VA · On-site +1

$129K - $155K/yr

TS/SCI with Poly Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking an AI Data Engineer to join our team at Fort Belvoir, Virginia. The AI Data Engineer will design, develop, and ...

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Ai Data Annotation Remote information

What is an AI Data Annotation Remote job?

An AI Data Annotation Remote job involves labeling, tagging, or categorizing data used to train artificial intelligence models. Annotators work with text, images, audio, or video to ensure machine learning algorithms receive accurate and high-quality input. This role is performed remotely, allowing flexibility in work location and schedule. Attention to detail, consistency, and familiarity with annotation tools are essential skills for this job.

What does a typical day look like for someone working remotely in AI data annotation?

A typical day for a remote AI Data Annotation worker involves reviewing and labeling various types of data such as images, text, or audio according to specific guidelines provided by the employer or project lead. You may use specialized annotation software and work through batches of data while following quality standards and deadlines. Periodic team check-ins or virtual meetings help clarify instructions, address questions, and monitor progress. While most of the work is independent, communication with supervisors or quality assurance teams is important to ensure that data labeling is consistent and accurate.

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

To thrive as an AI Data Annotation Remote worker, you need strong attention to detail, familiarity with data labeling processes, and a basic understanding of machine learning concepts, often supported by a high school diploma or relevant experience. Familiarity with data annotation platforms such as Labelbox, Supervisely, or AWS SageMaker Ground Truth is typically required, and certifications in data annotation or AI may be advantageous. Strong time management, the ability to work independently, and clear communication skills are valuable in this remote role. These abilities ensure accurate and efficient data labeling, which is critical for training reliable AI models.

What are the most commonly searched types of Ai Data Annotation jobs in Washington? The most popular types of Ai Data Annotation jobs in Washington are:
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Infographic showing various Ai Data Annotation Remote job openings in Washington as of June 2026, with employment types broken down into 62% Full Time, 17% Part Time, 10% Temporary, and 11% Contract. Highlights an 100% Remote job distribution.
AI Data Engineer

AI Data Engineer

SAIC

Fort Belvoir, VA • On-site, Remote

$129K - $155K/yr

Full-time

Posted 9 days ago

SAIC rating

7.9

Company rating: 7.9 out of 10

Based on 79 frontline employees who took The Breakroom Quiz

66th of 206 rated it services

Job description

Job ID: 2612714

Location: Fort Belvoir, VA, US

Date Posted: 2026-05-18

Category: Information Technology

Subcategory: Database Engr

Schedule: Full-Time

Shift: Day Job

Travel: Yes - 10% of the time

Minimum Clearance Required: TS.SCI

Clearance Level Must Be Able to Obtain: TS/SCI with Poly

Potential for Remote Work: ORA_ON_SITE


Description

SAIC is seeking an AI Data Engineer to join our team at Fort Belvoir, Virginia.

The AI Data Engineer will design, develop, and maintain data pipelines and architectures to support AI/ML workloads for the Army Intelligence & Security Enterprise (AISE). This role ensures data availability, quality, security, and operational integration to enable advanced analytics and decision-making. The AI Data Engineer will collaborate with cross-functional teams, optimize data workflows, and contribute to intelligence solutions.
Key Responsibilities:

  • Translate business requirements into logical data models to support entity relationships and data flows.
  • Design and implement scalable data pipelines for AI and machine learning workloads.
  • Develop and maintain data architectures to ensure data quality, availability, and security.
  • Collaborate with internal teams and external stakeholders to meet AI/ML data requirements.
  • Optimize data workflows for real-time analytics and decision-making.
  • Ensure adherence to data governance policies and security protocols.
  • Stay current on data engineering, AI, and machine learning advancements.
  • Support the operational deployment and integration of AI/ML solutions to enhance intelligence capabilities.
  • Analyze complex data challenges and deliver practical, innovative technical solutions aligned with organizational goals.
  • Engage frequently with internal and external stakeholders to resolve technical issues and deliver impactful solutions.
  • Contribute to the successful delivery of programs and projects.

Qualifications

Required Education:

  • Bachelors degree and five (5) years or more related experience; Masters and two (2) years or more experience; PhD or JD and zero (0) years or more experience.

Qualifications:

  • 5+ years of experience in systems engineering, data engineering, data architecture, or similar roles.
  • Expertise with Palantir Foundry; particularly with Ontologies, Object Types, Data Pipelines, and AIP tools).
  • Strong knowledge of data pipeline design, ETL processes, and database management.
  • Proficiency in programming languages such as Python, SQL, and TypeScript; and object-oriented development.
  • Experience utilizing Large Language Models (LLMs) for tasks like NLP, text generation, and conversational AI.
  • Familiarity with data governance, security practices, and compliance standards.
  • Excellent analytical, problem-solving, and teamwork abilities.

Desired Qualifications:

  • Experience with Apache Spark or other distributed computing platforms.
  • Palantir Foundry Certification.
  • Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, AWS SageMaker).
  • Proficiency in real-time data processing and analytics platforms.
  • Knowledge of Army Intelligence Enterprise data workflows and requirements.
  • Strong understanding of MLOps practices and supporting tools.
  • Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud).

Clearance:

  • Candidate must have an active TS/SCI clearance with the ability to obtain a TS/SCI with Poly.  
     

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