Consultant Machine Learning & Knowledge Graph Engineer
AI summary of the role
Lead architecture and delivery of enterprise-scale ML and knowledge graph systems at Dell, driving MLOps standards and building production-grade graph platforms (Neo4j/Stardog) that power agentic AI and GenAI applications.
What you’ll do
- Lead end-to-end agentic lifecycle: conceptualize, prototype, and deliver autonomous AI agents, ML systems, pipelines, and inference services.
- Design, build, and scale enterprise Knowledge Graph platforms using Neo4j and/or Stardog, establishing graph-native data models for entity resolution and semantic reasoning.
- Define and govern enterprise ontologies (OWL 2), taxonomies, and semantic schemas for unified, machine-interpretable data views.
- Architect graph-backed RAG systems, tool-calling interfaces, and prompt-to-graph query pipelines for autonomous AI agents.
What you’ll bring
- 12+ years delivering complex AI/ML or applied science systems, including deep learning, ML, and LLM-based solutions.
- Advanced Python expertise with ETL pipelines (Airflow preferred) and modern data-warehousing concepts.
- Hands-on production-grade graph systems experience with Neo4j (Cypher, GDS, APOC, AuraDB, Causal Clustering) and/or Stardog (SPARQL, OWL 2 reasoning, Virtual Graphs, SHACL validation).
- Expert-level PySpark, Kafka, data lakehouses (Apache Iceberg, Delta Lake), and enterprise orchestration (Airflow).
Technologies
Neo4j · Stardog · Cypher · SPARQL · OWL 2 · PySpark · Kafka · Apache Iceberg · Delta Lake · Airflow · Docker · Kubernetes
About Dell Technologies
Dell sells servers, storage, networking, and PCs to enterprises and consumers worldwide, with a fast-growing AI Factory infrastructure business.
Public · 5000+ people
Source and classification
Internal deployment & tooling · Evidence for this classification:
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
More from the 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, includin [... source excerpt omitted ...] nologies 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 [... source excerpt omitted ...] ng 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-Aug
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