ZipRecruiter

Log In

1

Manager Knowledge Graph Jobs (NOW HIRING)

Salesforce, Inc.

Principal Knowledge Engineer

Manhattan, NY · On-site

$197.30 - $313.70/hr

Establish enterprise standards, governance models, engineering patterns, and best practices for Knowledge Graph development, deployment, and lifecycle management.* Define strategies for integrating ...

previous page

Showing results 41-60

All JobsTechnology JobsInformation Technology JobsIT Manager JobsManager Knowledge Graph Jobs

Manager Knowledge Graph information

See salary details

$9

$26

$54

How much do manager knowledge graph jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for manager knowledge graph in the United States is $26.35, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $32.69 per hour, depending on experience, location, and employer.

What is the difference between Manager Knowledge Graph vs Data Analyst?

AspectManager Knowledge GraphData Analyst
Required CredentialsBachelor's degree in Computer Science, Data Science, or related field; knowledge of graph databasesBachelor's degree in Statistics, Mathematics, or related field; proficiency in data analysis tools
Work EnvironmentCollaborative teams, often in tech or data-driven companiesOffice setting, analyzing data sets, creating reports
Industry UsageUsed in AI, semantic web, knowledge management projectsUsed across finance, marketing, healthcare for data insights

The Manager Knowledge Graph focuses on designing and managing knowledge graph systems, requiring expertise in graph databases and data modeling. Data Analysts primarily interpret data to generate insights, using statistical tools. While both roles work with data, the Manager Knowledge Graph is more technical and system-oriented, whereas Data Analysts focus on data interpretation and reporting.

What cities are hiring for Manager Knowledge Graph jobs?

Cities with the most Manager 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 Manager Knowledge Graph jobs?

States with the most job openings for Manager Knowledge Graph jobs include:

Manager Knowledge Graph jobs near you

Consultant Machine Learning & Knowledge Graph Engineer

Dell, Inc.

Round Rock, TX • On-site

Full-time

Re-posted 9 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