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How much do knowledge graph jobs pay per hour?

As of Jul 6, 2026, the average hourly pay for knowledge graph in the United States is $31.03, according to ZipRecruiter salary data. Most workers in this role earn between $15.87 and $25.96 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Knowledge Graph position, and why are they important?

To thrive as a Knowledge Graph Engineer, you need strong skills in semantic web technologies, ontology modeling, and data integration, typically supported by a background in computer science or data science. Familiarity with tools like RDF, SPARQL, OWL, and knowledge graph platforms (e.g., Neo4j, GraphDB) is common, and certifications in data engineering or semantic technologies are beneficial. Effective communication, problem-solving abilities, and cross-functional collaboration are valuable soft skills in this field. These competencies are crucial for designing, implementing, and maintaining knowledge graphs that enable advanced data discovery and insights for organizations.

Is ML a high paying job?

Machine Learning (ML) roles, including positions like ML engineer or data scientist, are generally well-paid due to the specialized skills required, such as programming, statistics, and knowledge of algorithms. Salaries tend to be higher than average in tech hubs and often increase with experience, certifications, and proficiency in tools like Python, TensorFlow, or PyTorch.

What is a knowledge graph job description?

A knowledge graph job description typically involves designing, developing, and maintaining knowledge graphs that organize and connect data for improved search, reasoning, and data integration. The role often requires skills in data modeling, graph databases like Neo4j, and understanding of semantic technologies such as RDF and OWL. Professionals in this field may work with data scientists, software engineers, and domain experts to ensure accurate and efficient knowledge representation.

What is a Knowledge Graph job?

A Knowledge Graph job typically involves designing, building, and maintaining structured representations of data that map relationships between entities. Professionals in this role work with technologies like RDF, SPARQL, ontologies, and graph databases to enhance data integration, retrieval, and reasoning. These jobs are common in AI, search, and data science fields, helping organizations improve knowledge discovery and decision-making.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, senior machine learning engineer, or AI product executive, often requiring advanced skills in data science, programming, and deep learning. These roles usually involve leadership, strategic planning, and expertise in tools like TensorFlow or PyTorch, with compensation reflecting experience and impact. Such salaries are rare and generally found in top tech companies or specialized AI firms.

What engineer makes $500,000 a year?

Senior data engineers or machine learning engineers working in high-demand industries such as technology, finance, or AI can earn salaries around $500,000 annually, especially with extensive experience, advanced skills in big data tools, and relevant certifications. Compensation varies based on location, company size, and individual expertise.

What are some typical daily responsibilities of a Knowledge Graph Engineer?

As a Knowledge Graph Engineer, your typical day involves designing and developing ontologies, integrating diverse data sources, and implementing graph-based data models to enhance information accessibility. You may work closely with data scientists, software developers, and business analysts to gather requirements and translate them into scalable knowledge graph solutions. Regular tasks include writing SPARQL queries, performing data mapping, maintaining documentation, and troubleshooting graph data issues. Collaboration and ongoing learning are integral as this field rapidly evolves with new tools and best practices.

More about Knowledge Graph jobs
What cities are hiring for Knowledge Graph jobs? Cities with the most Knowledge Graph job openings:
What are the most commonly searched types of Knowledge Graph jobs? The most popular types of Knowledge Graph jobs are:
What states have the most Knowledge Graph jobs? States with the most job openings for Knowledge Graph jobs include:
What job categories do people searching Knowledge Graph jobs look for? The top searched job categories for Knowledge Graph jobs are:
Knowledge Graph jobs near you
Infographic showing various Knowledge Graph job openings in the United States as of June 2026, with employment types broken down into 1% Full Time, 89% Part Time, 9% Contract, and 1% Nights. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $64,550 per year, or $31 per hour.
Generative AI Engineer (Knowledge Graph)

Generative AI Engineer (Knowledge Graph)

HTC Global Services

Dearborn, MI • On-site

$89K - $122K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 26 days ago

Job description

Job Title
Knowledge Graph & Generative AI Engineer
Overview / Summary
We are seeking a Knowledge Graph & Generative AI Engineer to work at the intersection of semantic data engineering, graph systems, and generative AI. This role focuses on transforming unstructured data into interconnected Knowledge Graphs (KGs) that support Retrieval-Augmented Generation (RAG), recommendation engines, and advanced reasoning models.
Key Responsibilities
• Design, build, and optimize scalable graph databases using technologies such as Neo4j and TigerGraph.
• Map ontologies and semantic web standards, including RDF and OWL.
• Develop embedding ingestion pipelines and integrate Knowledge Graphs with Large Language Models (LLMs).
• Enhance contextual retrieval, search capabilities, and generative AI responses through AI/LLM integration.
• Build and manage data processing approaches that parse and transform structured and unstructured data into graph-oriented formats.
• Architect entity resolution and relationship extraction workflows.
• Develop machine learning workflows to identify patterns and dependencies within complex datasets.
Required Qualifications
• Experience designing, building, and optimizing graph databases.
• Knowledge of graph technologies such as Neo4j or TigerGraph.
• Understanding of semantic web standards, including RDF and OWL.
• Experience developing embedding ingestion pipelines.
• Experience integrating Knowledge Graphs with Large Language Models (LLMs).
• Ability to process and transform structured and unstructured data into graph-oriented formats.
• Experience with entity resolution and relationship extraction.
• Experience developing machine learning workflows for complex data analysis.
What Makes HTC A Great Place To Build Your Future
HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you'll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You'll have long-term opportunities to grow your career and develop skills in the latest emerging technologies.
At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks.
Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.
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