Storage AI Engineer
Hewlett Packard Enterprise (HPE)Match Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessLog in to see why each signal reads the way it does.
Job Description
Structured overview of role & requirementsAbout This Role
Design and build production-grade AI and Generative AI solutions with large language models (LLMs) including AI agents, workflow automation, and Retrieval-Augmented Generation (RAG) systems.
Fine-tune, evaluate, optimize, and deploy AI/ML models to deliver scalable, reliable AI-powered storage platform features.
Establish monitoring and governance for responsible AI deployment and drive AI technology adoption across the organization.
Minimum Requirements
Bachelor's or master's degree in computer science, engineering, or a closely related quantitative discipline.
3-5 years of relevant experience in AI/ML software engineering or related fields.
Mandatory technical skills: Python, SQL, Java or Go; PyTorch, Scikit-learn, LangChain; Generative AI knowledge including GPT, Claude, Llama, prompt engineering, fine-tuning, RAG, agentic AI, vector databases.
Experience with cloud and MLOps technologies: AWS/Azure, Kubernetes, Docker, MLflow, CI/CD; Hybrid work mode with approx. 2 days/week in office.
Ideal Candidate Profile
Strong expertise in building scalable AI-powered products for enterprise storage or cloud platforms, integrating advanced AI models into production environments.
Experience collaborating cross-functionally with data scientists and engineers to translate AI research into operational solutions.
Comfortable working in hybrid cloud and MLOps environments, with an operational focus on responsible AI governance and model lifecycle management.