Machine Learning & Knowledge Graph Engineer

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.