ZipRecruiter

Log In

1

Knowledge Graph Jobs (NOW HIRING)

next page

Showing results 1-20

All JobsKnowledge Graph Jobs

Knowledge Graph information

See salary details

$9

$31

$119

How much do knowledge graph jobs pay per hour?

As of Jul 24, 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 July 2026, with employment types broken down into 1% Locum Tenens, 61% Full Time, 33% Part Time, 3% Contract, and 2% Summer. Highlights an 55% Physical, 3% Hybrid, and 42% Remote job distribution, with an average salary of $64,550 per year, or $31 per hour.
Consultant Machine Learning & Knowledge Graph Engineer

Consultant Machine Learning & Knowledge Graph Engineer

Dell, Inc.

Round Rock, TX • On-site

Full-time

Posted 10 days ago

Job description


Consultant Machine Learning & Knowledge Graph Engineer
Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. What's more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data.
Join us to do the best work of your career and make a profound impact as Consultant ML & KG Engineer on our growing and dynamic team in Round Rock, Texas.
What you'll achieve
Lead the architecture, development, and deployment of enterprise scale ML solutions across Dell's global ecosystem. Drive MLOps standards, build production grade ML services, and collaborate across engineering, product, and platform teams to enable AI at scale.scale ML solutions across Dell's global ecosystem. As a Consultant Machine Learning & Knowledge Graph Engineer, you will play a pivotal role in advancing our AI and ML capabilities and creating Enterprise wide KG marketplace and Ontology layouts. You will be responsible for designing, building, and operationalizing machine learning systems, including next generation agentic and GenAI powered applications. You will drive and execute our broader AI/ML strategy. You will also be responsible to architect production-grade Knowledge Graph platforms, design semantic data layers that power Agentic AI, and drive the convergence of graph technologies with large-scale data engineering ecosystems. This role demands a rare combination of deep graph expertise, distributed systems mastery, and strategic business influence. You will work deeply across data pipelines, model development, optimization, and production deployment to deliver scalable, high performance ML solutions.
You will
  • Lead the end-to-end Agentic lifecycle-from conceptualizing, prototyping and driving delivery with engineering teams and design and build autonomous AI agents, ML systems, pipelines, and inference services.
  • Work with business leads to imagine agentic products and drive accelerated delivery through Spec Driven Development and implement MLOps practices including CI/CD, model monitoring, drift detection, and automated retraining.
  • Collaborate with Data Engineering and Platform teams to ensure data, infrastructure, and governance readiness along with providing technical leadership while integrating emerging AI/ML technologies and managing production incidents.
  • Design, build, and scale enterprise Knowledge Graph platforms using Neo4j and/or Stardog, establishing graph-native data models that enable entity resolution, relationship discovery, and semantic reasoning across business domains.
  • Define and govern enterprise ontologies (OWL 2), taxonomies, and semantic schemas that provide a unified, machine-interpretable view of Dell's data assets, ensuring consistency, reusability, and inferencing capability
  • Architect graph-backed Retrieval-Augmented Generation (RAG) systems, tool-calling interfaces, and dynamic prompt-to-graph query pipelines that fuel autonomous AI agent decision-making with deterministic, explainable knowledge

Take the First Step Towards Your Dream Career
Every Dell Technologies team member brings something unique to the table. Here's what we are looking for with this role:
Essential Requirements:
  • 12+ years of experience delivering complex AI/ML or applied science systems, including deep learning, machine learning, and LLM-based solutions.
  • Advanced Python expertise with strong knowledge of ETL pipelines (Airflow preferred) and modern data-warehousing concepts.
  • Graph Architecture Mastery: Extensive hands-on experience designing and operating production-grade graph systems using Neo4j (Cypher, GDS, APOC, AuraDB, Causal Clustering) and/or Stardog (SPARQL, OWL 2 reasoning, Virtual Graphs, SHACL validation)
  • Distributed Systems and Data Scale: Expert-level command over PySpark, Kafka, data lakehouses (Apache Iceberg, Delta Lake), and enterprise orchestration (Airflow), with proven ability to integrate these with graph ecosystems
  • Strong software engineering background with hands-on experience in AI frameworks, cloud environments, and domains such as ML, NLP, IR, recommender systems, and LLMs and proven experience with Docker, Kubernetes, and major cloud platforms (AWS/GCP/Azure), including training, fine-tuning, and applying LLMs for agentic AI applications.

Desirable Requirements
  • PhD or Master's degree in Technology, Computer Science, Machine Learning or equivalent quantitative field
  • Familiarity leveraging graph-based techniques, semantic search, hybrid search systems, and implementing solutions that combine traditional IR methods with machine learning models to enhance search relevancy accuracy and efficiency. Familiarity with large scale data handling when dealing with telemetry systems.
DELL logo

About DELL

Sourced by ZipRecruiter

Dell Technologies helps organizations and individuals build a brighter digital tomorrow. Our company is made up of more than 150,000 people, located in over 180 locations around the world. We're proud to be a diverse and inclusive team and have an endless passion for our mission to drive human progress.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Round Rock, TX, US

Year founded

1984

View All DELL Jobs

Apply