AI Solutions Development Engineer

What you’ll achieve

As an AI Solutions Development Engineer, you will be responsible for the engineering work necessary to develop Dell Integrated Solutions based on the Generative AI-based compute, network, and storage infrastructure environment. You will work closely with multiple Dell stakeholders to ensure all engineering solutions projects align with Dell Technologies’ AI strategy. Our Solutions Development Engineers operate at the cutting edge of technological advancements.

We design and develop AI and GenAI solutions integrating GPU accelerated compute, network, and storage products, in Slurm and Kubernetes clustered environments, allowing data scientists and developers to develop, fine tune, customize and deploy (for inference) AI models towards various use‑cases and deployment environments (core, edge, cloud and anything in between).

• Review requirements and develop test plans based on the Generative AI solution specifications and Product Manager’s Product Requirements Document
• Configure, deploy, and test AI workloads running on the Generative AI environment; critical responsibilities of the role are to troubleshoot and resolve issues, conduct technical reviews of all deliverables, and continually communicate project status to all relevant stakeholders
• Examine and evaluate internal and external engineering‑specific documentation related to projects; you will share knowledge with peers and leaders to improve internal processes and drive ideas to streamline future development work
• Utilize your expertise to assist in the development of technical customer and partner content such as design guides, sizing guides, technical white papers, implementation guides, technical blogs

• 8+ years’ professional Engineering experience developing and deploying end‑to‑end (infrastructure to platform to application to workload to use‑cases solutions is highly desired)
• Knowledge in infrastructure deployment and the hardware ecosystem e.g., servers, storage, and networking (to include IP addressing, subnets, VLANs etc.)
• Solid understanding of Linux‑based operating systems (deployment and configuration) and cluster management (including deploying and managing containers, Kubernetes and Slurm clusters)
• Excellent collaboration, communication, and presentation skills; must be able to work with all levels of the organization and effectively communicate status of development work to relevant stakeholders in a consistent and timely manner

• Familiarity of AI Technologies e.g., Generative/Cognitive AI framework/models, Machine Learning/Deep Learning, AI platforms/libraries (e.g., Hugging Face, Tensor Flow) and Open‑Source Machine Learning framework (PyTorch)
• Degree in a quantitative field (Computer Science, Mathematics, Statistics, Electrical Engineering, Physical Sciences, etc.)

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