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Remote Ai Operator Jobs in Virginia (NOW HIRING)

Kobie Marketing

AI Engineer

Richmond, VA · Remote

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... and operating services * 1+ years of hands-on work with LLMs in production: prompt/context ...

Aris

Executive Value Advisor (USA remote)

Reston, VA · On-site +1

Understanding of how AI/agentic AI is reshaping process landscapes and operating models * Ability to bridge business architecture with solution capabilities * Exceptional presentation and ...

Booz Allen Hamilton, Inc.

Penetration Tester

Herndon, VA · On-site +1

$86K - $198K/yr

Remote Work: No Job Number: R0236401 Location: Herndon,VA,US Share job via: Share Penetration ... Knowledge of tools, tactics, and techniques targeting Artificial Intelligence (AI) systems and ...

Lokalise

Head of Partnerships

Virginia Beach, VA · Remote

Our AI-powered localization platform helps companies manage both software and marketing content ... This is a full-time, remote position. Please note that we do not engage on a B2B or contractor ...

Booz Allen Hamilton, Inc.

TAK Developer, Senior

Mclean, VA · On-site +1

$86K - $198K/yr

Remote Work: No Job Number: R0241334 Location: McLean,VA,US Share job via: Share TAK Developer ... Candidate AI Usage Policy AI is a part of our daily work at Booz Allen, and we are committed to the ...

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Remote Ai Operator information

What is the difference between Remote Ai Operator vs Data Labeler?

AspectRemote Ai OperatorData Labeler
Required CredentialsBasic technical skills, sometimes certifications in AI toolsMinimal; often no formal credentials needed
Work EnvironmentRemote, tech-focusedRemote or on-site, often repetitive tasks
Industry UsageAI development, machine learning projectsData preparation for AI models
Common Search/ComparisonYesNo

Remote Ai Operators typically work on managing AI systems and require some technical knowledge, whereas Data Labelers focus on annotating data with minimal credentials. Both roles are remote and essential in AI development, but they differ in complexity and responsibilities.

How does a Remote AI Operator typically collaborate with cross-functional teams in a distributed work environment?

As a Remote AI Operator, collaboration with data scientists, engineers, and product managers is often facilitated through digital communication tools such as Slack, Zoom, and project management platforms. Regular virtual meetings and asynchronous updates are common, ensuring alignment on project goals and rapid issue resolution. Operators are expected to provide feedback on AI model performance, flag anomalies, and contribute to workflow improvements, all while adapting to different time zones and communication styles. This collaborative approach helps maintain high-quality AI system outputs and supports continuous improvement.

What are the key skills and qualifications needed to thrive as a Remote AI Operator?

To thrive as a Remote AI Operator, you need a solid understanding of artificial intelligence concepts, data processing, and typically a background in computer science or a related field. Experience with AI platforms (such as TensorFlow or PyTorch), cloud computing tools, and sometimes certifications in machine learning or data analysis are commonly required. Strong problem-solving abilities, attention to detail, and effective remote communication skills set top performers apart. These skills ensure accurate AI system management, timely troubleshooting, and seamless collaboration with distributed teams.

What is a Remote AI Operator?

A Remote AI Operator is a professional who oversees, manages, and sometimes directly interacts with artificial intelligence (AI) systems from a remote location. Their role often includes monitoring AI performance, troubleshooting issues, ensuring data integrity, and making adjustments to improve outcomes. Remote AI Operators may work in industries like customer service, manufacturing, healthcare, or autonomous vehicles. They typically use specialized software tools to interface with AI applications, ensuring the technology is operating as intended. This position often requires strong analytical skills and familiarity with AI platforms or machine learning concepts.
What are the most commonly searched types of Ai Operator jobs in Virginia? The most popular types of Ai Operator jobs in Virginia are:
What are popular job titles related to Remote Ai Operator jobs in Virginia? For Remote Ai Operator jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Ai Operator jobs in Virginia look for? The top searched job categories for Remote Ai Operator jobs in Virginia are:
What cities in Virginia are hiring for Remote Ai Operator jobs? Cities in Virginia with the most Remote Ai Operator job openings:
Remote Ai Operator jobs near you

Semantic Data and AI Engineer

Enterprise Knowledge

Arlington, VA • On-site, Remote

$131K - $158K/yr

Full-time

Re-posted 22 days ago

Job description

Enterprise Knowledge (EK) is hiring a full-time Semantic Data and AI Engineer to join our growing Semantic Engineering and AI Practice. In this role, you will be responsible for designing and deploying cutting-edge data discovery, integration, and governance solutions for a wide range of organizations around the world.
The Semantic Data and AI Engineer will be part of a team working on innovative projects and developing orchestrated data solutions to integrate, enrich, and transform a range of knowledge assets (structured and unstructured) for Artificial Intelligence (AI) solutions. This individual will be able to quickly learn new technologies and apply them to business challenges at large corporations, organizations, and federal agencies. The right candidate will have a passion for working with diverse data types and applying new methods and approaches to data challenges with a strategic mindset to advise clients on enterprise AI transformations.
As an EKer, you will join a fast-growing company that is committed to equity and inclusion, have the opportunity to work in a collaborative workplace, take advantage of our unique benefits, and help build our innovative culture. To read more about the impactful work we are doing and to see the latest thought leadership from EK, follow us on LinkedIn.
Responsibilities
  • Work with data subject matter experts and business users to effectively understand and model their domain of knowledge
  • Apply NLP techniques (entity extraction, classification, and document processing) to transform raw data and content into AI-ready assets
  • Design, implement, test, and operate end-to-end RAG workflows for client engagements, including retrieval pipeline architecture, embedding strategies, and response evaluation
  • Contribute to agentic AI solution design and implementation, including orchestration patterns, tool use, and memory and retrieval integration
  • Support a variety of business intelligence projects using AI-based solutions
  • Analyze complex datasets and communicate insights to both technical and non-technical stakeholders
  • Design and implement data pipelines for ingesting, processing, and enriching structured and unstructured content using SQL, Python, R, or equivalent languages
  • Contribute to semantic layer and knowledge graph implementations as part of larger AI solution architectures
  • Work with internal and external teams to contextualize data engineering work into larger project context

Requirements
As a federal contractor, Enterprise Knowledge will not sponsor a new applicant for employment authorization or offer any immigration related support for this position (i.e,. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1, and O-1, or any EADs or other forms of work authorization that require immigration support from an employer.
Our office is located in Arlington, VA, and operates on a hybrid model. While local candidates are preferred, we are also able to hire remote candidates residing in the following states: CO, FL, MA, NC, NH, NM, NY, OR, PA, RI, TX, and WA.
Required Skills and Experience:
  • Bachelor's degree in math, statistics, economics, data science, computer science, or a related field
  • 5+ years experience working on data analysis project(s) designing reports, and designing data analysis approaches and visualizations in a production setting
  • Proven experience working directly with clients, providing briefings, facilitating meetings, and presenting work products
  • Experience applying machine learning methods and statistical analysis to business use cases
  • Proficiency in programming languages such as Python, R, or similar for data analysis and modeling
  • Experience with NLP methods: entity extraction, text classification, document processing, or similar techniques applied to unstructured data in a production setting
  • Hands-on experience building and optimizing RAG pipelines, including embedding strategies, reranking, and cross-encoder models
  • Familiarity with retrieval quality and evaluation metrics (precision, recall, MRR, and user-centric evaluation approaches)
  • Experience implementing monitoring and observability for RAG and AI components, including latency, success rate, cache hit rate, retrieval quality, and data drift
  • Familiarity with data modeling, database architecture, and data integration, aggregation, and normalization across heterogeneous sources
  • Interest in developing as a consultant and taking on additional responsibilities for delivering and growing work
Preferred Skills and Experience:
  • Experience designing and working with relational databases
  • Experience designing and working with graph databases and SPARQL
  • Experience with AI governance practices covering model monitoring, evaluation frameworks, and access entitlements
  • Comfortable working with containerized environments; Docker proficiency expected, Kubernetes familiarity a plus
  • Experience with cloud platforms (AWS, Azure, or GCP) for deploying and operating AI and data solutions
  • Exposure to ontology or taxonomy design, and familiarity with taxonomy/ontology management tools (Progress Semaphore, PoolParty, Synaptica, Mondeca, etc.)
  • Experience designing and planning data science projects to meet business requirements
  • Experience implementing agentic AI workflows using frameworks such as LangChain, LlamaIndex, LangGraph, BAML, or equivalent
Salary Information:
EK considers a broad range of factors in considering employee salary, including a candidate's skills, experience, education, certifications, past successes, and qualifications. The salary range for this role is $150,000 to $210,000, with most candidates likely to fall in the lower half. This range does not guarantee a specific salary and may be adjusted based on the needs of the company and the candidate's qualifications.
Data Privacy Notice:
Enterprise Knowledge (EK) is committed to protecting your personal information. When you submit your application, we collect and process your personal data solely for recruitment and hiring purposes. We will not use your information for any other purpose without your explicit consent.
We may share your information with third parties only as necessary to evaluate your application or comply with legal requirements. If we need to use your data for a purpose beyond the original intent or disclose it to additional third parties, we will provide you with prior notice.
You have the right to access the personal information we hold about you and to request corrections, amendments, or deletion of any inaccurate data or data processed in violation of applicable privacy principles. Requests for such changes will be reviewed and accommodated unless the burden or expense of providing access would be disproportionate to the risks to your privacy, or where the rights of other individuals may be affected.
By submitting your application, you acknowledge that you have read and understood this notice. If you have any questions about how we handle your personal data or need to update your information, please contact us at careers@enterprise-knowledge.com.

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