Hybrid ML Research Engineer (Post-doc) – Digital Twin & RL

Hewlett Packard Enterprise; Dublin; Hybrid; EUR 90,000 - 120,000; Full time

Benefits offered by this job

Hybrid work policy

Job summary

Hewlett Packard Enterprise, through its HPE Labs Ireland, is seeking a machine-learning research engineer to advance AI-driven digital twins for data-centre operations. You will transform research into deployed technology, focusing on reinforcement learning, time-series forecasting, and sustainability.

The role spans research, software engineering and experimentation, with collaboration across international partners.

Qualifications

• PhD or Masters in a relevant field with research experience.
• Strong Python and PyTorch software development skills.
• Experience applying ML to physical systems and digital twins.
• Proven ability to lead independent research and communicate clearly.

Responsibilities

• Build and evolve digital-twin software integrating telemetry and physical models.
• Develop probabilistic forecasts for IT load, cooling demand and related signals.
• Research, train and evaluate multi-objective reinforcement-learning policies.
• Implement a price-response interface with uncertainty information.
• Validate control stacks with hardware-in-the-loop, shadow and live trials.
• Produce evidence of performance including KPI analysis and M&V workflows.
• Collaborate with HPE Labs and AIRL partners to integrate results into the controller.
• Provide technical leadership and transfer technology to practice.

Skills

Python

PyTorch

Machine learning

Digital twins

Time-series

Education

PhD or Master’s degree in CS/Engineering

Research publications

Job description

Hewlett Packard Enterprise, through its HPE Labs Ireland, is seeking a machine-learning research engineer to advance AI-driven digital twins for data-centre operations. You will transform research into deployed technology, focusing on reinforcement learning, time-series forecasting, and sustainability.

The role spans research, software engineering and experimentation, with collaboration across international partners.