Principal Engineer, Storage Data Science and Analytics
Core
Principal technical authority bridging machine learning, GenAI, and big data analytics with HPE's next-generation cloud and storage ecosystem to extract intelligence from telemetry data pipelines.
Role type
Principal Engineer, Storage Data Science and Analytics
Builds
Predictive AI models for storage optimization, automated mitigation systems, and agentic workflows for customer support analytics.
Domain
Enterprise storage, hybrid cloud, and data science
Deliverable
production ML models
Required skills
Machine learning algorithms, deep learning frameworks, Python, Go, distributed systems, storage architectures, LLM fine-tuning, vector databases, time-series forecasting, anomaly detection
Preferred skills
C/C++, system internals, prompt engineering, RAG, agentic systems, whitepaper/patent generation
Technologies
Kafka, Spark, GreenLake
Responsibilities
Define organization-wide data architecture strategy, develop predictive AI models for storage optimization, validate distributed telemetry data, design and scale ML code in production environments, establish ELT patterns and streaming pipelines, mentor senior engineers and data scientists
Seniority
Principal, hands-on IC with strategy & mentorship