AI Research Scientist

• Build the CIC data and workload pipeline, including controlled workload generation, telemetry ingestion, time-series data management, data-quality checks, and baseline datasets
• Develop modular digital-twin software combining site telemetry with physical models, empirical performance maps, cooling and storage models, and operational constraints
• Develop probabilistic forecasts for IT load, cooling demand, and relevant water and heat signals
• Research, implement, train, and evaluate objective-shifting multi-objective reinforcement-learning policies balancing flexibility, cost, carbon, water use, and durability within hard safety limits
• Implement a price-response interface producing feasible, auditable flexibility commitments with uncertainty information
• Validate the control stack through replay, hardware-in-the-loop testing, shadow mode, and controlled actuation windows on CIC MODPODs
• Produce reproducible evidence for flexibility, reliability, sustainability, and durability performance, including measurement-and-verification workflows and KPI analysis
• Collaborate with HPE Labs researchers and AIRCAS partners to integrate laboratory cooling results, sustainability signals, and physical operating guardrails
• Take innovative ideas from conception through design, development, implementation, evaluation, and technology transfer
• Collaborate with HPE Labs teams, external partners, and HPE's wider innovation community

Explore Machine Learning/AI Research Engineer – Post-doc at Hewlett Packard Enterprise. Review requirements and application details.