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Remote Ontology Engineer Jobs (NOW HIRING)

NTT DATA Services

Ontology Expert - Remote

Dallas, TX · On-site +1

... AI engineers to translate knowledge into formal models. - Govern ontology lifecycle, versioning ... The starting pay range for this remote role is $105,840.00-$147,000.00. This range reflects the ...

NTT DATA Services

Ontology Expert - Remote

Dallas, TX · Remote

... AI engineers to translate knowledge into formal models. - Govern ontology lifecycle, versioning ... The starting pay range for this remote role is $105,840.00-$147,000.00. This range reflects the ...

NTT DATA Services

Ontology Expert - Remote

Dallas, TX · Remote

... AI engineers to translate knowledge into formal models. - Govern ontology lifecycle, versioning ... The starting pay range for this remote role is $105,840.00-$147,000.00. This range reflects the ...

NewGen Technologies

This role is an early opportunity, expecting to allow remote work up to 100%. Serve as a resident ... RDF/OWL ontology engineering * SPARQL query development and optimization * Federated query design ...

Futran Tech Solutions Pvt. Ltd.

Software Engineer

Role: Software Engineer Location: Remote Duration: 6+ Months Required Skills * 8-10+ years of ... Experience working on Knowledge Graph or semantic systems, including ontology-driven design and ...

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How much do remote ontology engineer jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for remote ontology engineer in the United States is $53.63, according to ZipRecruiter salary data. Most workers in this role earn between $43.27 and $62.26 per hour, depending on experience, location, and employer.

What is a Remote Ontology Engineer?

A Remote Ontology Engineer is a professional who designs, develops, and maintains ontologies—structured frameworks for organizing information—while working from a remote location. They use their expertise in knowledge representation, semantic web technologies, and data modeling to ensure that information systems can interpret and connect data effectively. Their work is crucial in fields like artificial intelligence, data integration, and information retrieval, as they help systems 'understand' relationships between different pieces of data. Remote Ontology Engineers often collaborate with developers, data scientists, and domain experts using online tools and communication platforms.

What is the difference between Remote Ontology Engineer vs Data Scientist?

AspectRemote Ontology EngineerData Scientist
Required CredentialsMaster's in Computer Science, Knowledge Engineering, or related fields; certifications in ontology modelingDegree in Data Science, Statistics, or related; certifications in data analysis or machine learning
Work EnvironmentCollaborates with AI, semantic web, and knowledge management teams; often in tech or research industriesWorks with data analysis, modeling, and visualization teams; across various industries including tech, finance, and healthcare
Employer & Industry UsageUsed in AI, semantic web, and knowledge-based systemsApplied in analytics, predictive modeling, and business intelligence

While both roles require technical expertise and involve working with complex data, Remote Ontology Engineers focus on developing and managing ontologies for knowledge representation, whereas Data Scientists analyze data to extract insights. The roles often overlap in tech environments but serve different core functions.

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

To thrive as a Remote Ontology Engineer, you need a strong background in computer science, knowledge representation, and formal logic, typically supported by a relevant degree and experience in semantic technologies. Familiarity with ontology development tools (such as Protégé), semantic web standards (like OWL and RDF), and querying languages (SPARQL) is essential. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively in distributed teams and translate complex domain knowledge into structured ontologies. These skills are crucial for building robust, interoperable knowledge models that support data integration and intelligent applications across industries.

How does a Remote Ontology Engineer typically collaborate with cross-functional teams while working off-site?

As a Remote Ontology Engineer, you will frequently collaborate with data scientists, software developers, and subject matter experts through virtual meetings, shared documentation, and project management tools. Effective communication and proactive documentation are key, as you'll often need to clarify domain concepts and ensure semantic consistency across distributed teams. Many organizations use agile methodologies, so you can expect regular stand-ups and sprint planning sessions to stay aligned on project goals and deliverables. Building strong relationships remotely requires initiative, responsiveness, and a willingness to leverage digital collaboration platforms.
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Remote Ontology Engineer jobs near you
Infographic showing various Remote Ontology Engineer job openings in the United States as of May 2026, with employment types broken down into 99% Full Time, and 1% Part Time. Highlights an 78% Physical, 4% Hybrid, and 18% Remote job distribution, with an average salary of $111,552 per year, or $53.6 per hour.
Data Ontology Engineer

Data Ontology Engineer

General Dynamics Mission Systems, Inc

Remote

$142K - $158K/yr

Full-time

Posted 4 days ago

General Dynamics Mission Systems rating

8.2

Company rating: 8.2 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

75th of 186 rated software companies

Job description

Basic Qualifications
Bachelor's degree in Systems Engineering, or a related Science, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus a minimum of 6 years of relevant experience.
CLEARANCE REQUIREMENTS:: Department of Defense Secret security clearance is required at time of hire. Applicants selected will be subject to a U.S. Government security investigation and must meet eligibility requirements for access to classified information. Due to the nature of work performed within our facilities, U.S. citizenship is required.
Responsibilities for this Position
What You'll Own
  • Domain ontologies. Design and maintain semantic schemas that describe key engineering and manufacturing entities - products, BOMs, plants, equipment, processes, work orders - and their relationships across systems.
  • Knowledge graphs. Implement ontologies using semantic web or graph technologies (RDF/OWL/SHACL/SPARQL or property-graph equivalents like Neo4j). Build, query, validate, and tune knowledge graphs in production.
  • Data alignment. Integrate heterogeneous data sources - PLM, ERP, MES, CMMS, QMS, data lakes - into a common vocabulary. Align schemas, code sets, and master data to the ontology so AI services see one coherent picture.
  • Semantic layer. Design the enterprise semantic layer that BI tools, analytics platforms, and AI/LLM applications query consistently. Define core business entities, metrics, and hierarchies and map them to existing data stores.
  • Ontology governance. Manage versioning, documentation, reuse of industry standards, and enforcement of modeling best practices across pods. Your ontologies are shared assets - they must be maintainable by others.
What You Won't Own
  • AI model development or prompt engineering - you provide the data substrate, the AI engineers build on it
  • Enterprise system administration - you integrate data from systems, you don't manage them
  • Business process decisions - Domain SMEs and the Product Owner define what matters; you model it
What Makes This Role Different
  • Your ontologies directly feed AI systems that make real business decisions. A bad data model doesn't just slow a report - it makes an AI agent reason incorrectly.
  • You will work across multiple enterprise domains - HR, manufacturing, CRM, supply chain - building a shared knowledge architecture, not siloed data models.
  • You will collaborate with business SMEs who understand the domain and AI engineers who consume your models. You translate between both worlds.
Required Qualifications
  • Bachelor's degree in Computer Science, Data Science, Information Science, or a related field, plus 5 years of experience; or Master's degree plus 3 years of experience
  • Hands-on experience with knowledge graph or ontology technologies - RDF/OWL/SHACL/SKOS, SPARQL, and/or graph databases (Neo4j, Stardog, Ontotext, AWS Neptune, or similar)
  • Experience integrating disparate enterprise data sources into a shared vocabulary or knowledge graph - you have aligned data across systems that use different schemas, code sets, and terminology
  • Strong data modeling skills - dimensional modeling, semantic modeling, or formal ontology design applied in production, not just academic settings
  • Experience with enterprise data platforms - data warehouses, data lakes, Snowflake, Palantir Foundry, or similar
  • U.S. citizenship required. Department of Defense Secret security clearance is required at time of hire.
Preferred Qualifications
  • Experience building semantic layers or metrics layers consumed by BI, analytics, or AI/LLM applications
  • Experience with enterprise systems data (ERP, MES, PLM, CRM) - you understand the data structures these systems produce
  • Familiarity with AI/ML data requirements - embeddings, vectorization, retrieval-augmented generation, and how knowledge graphs support LLM reasoning
  • Comfortable leading workshops with non-technical business SMEs to capture requirements and iteratively refine data models
  • Experience with ontology governance - versioning, documentation, standards reuse across teams or an enterprise
What Sets You Apart
  • You think in relationships, not rows. You see connections between data that others model as flat tables.
  • You can explain a semantic model to a business SME and have them recognize their domain in it.
  • You build ontologies that other people can use and extend - not elegant models that only you understand.
  • You have integrated data from systems that were never designed to work together and made it coherent.
  • You care about data meaning, not just data structure. You know that two systems calling something "part number" doesn't mean they mean the same thing.
Details
  • Remote - 100% telework
  • 9/80 schedule
  • Defense industry experience is not required

Salary Note
This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled.
Combined Salary Range
USD $142,696.00 - USD $158,303.00 /Yr.
Company Overview
General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products and services that enable customers to successfully execute missions across all domains of operation. With a global team of 12,000+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high-performance team!
Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

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