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Machine Learning/AI Research Engineer – Post-doc
Hewlett Packard Enterprise. Build the CIC data and workload pipeline, including controlled workload generation, telemetry ingestion, time-series data management, data-quality checks, and baseline datasets .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing modular digital-twin software and implementing machine learning algorithms for physical systems, with a strong focus on sustainability and performance validation. Proven ability to lead independent research and collaborate effectively with interdisciplinary teams.
Highest-signal resume keywords
PhD Degree Or Master's Degree In Relevant DisciplineStrong Software-Development Skills In Python And PyTorchExperience Applying Machine Learning To Physical SystemsKnowledge Of Digital Twins And Sustainability ApplicationsIndependent Research Leadership With Publications
ATS Keywords
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Hard Skills
Machine LearningDeep LearningScientific ComputingEngineering ComputationProbabilistic Time-Series ForecastingReinforcement LearningData StructuresSystem-Level AnalysisModellingIntegrated Software Algorithms
Soft Skills
Excellent Research SkillsDevelopment SkillsWritten Communication SkillsVerbal Communication Skills
Tools & Technologies
PyTorchAI/ML PlatformsLarge-Scale ComputingData-Analysis EnvironmentsExperimental Systems
Industry Keywords
Digital TwinsSustainability ApplicationsMeasurement-And-Verification WorkflowsKPI AnalysisHardware-In-The-Loop Testing
Tech Stack
Tools & technologiesPythonPyTorch
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- PhD degree, or Master's degree with equivalent research and innovation experience, in a relevant discipline such as computer science, software engineering, electrical engineering, mathematics, physics, statistics, or mechanical engineering
- Proven record of innovation in deep learning, scientific computing, engineering computation, or machine-learning applications
- Demonstrated experience developing proofs of concept, first-of-a-kind solutions, or technologies for transfer into practice
- Evidence of independent research leadership, for example through publications in leading conferences or journals
- Strong software-development skills in Python and PyTorch
- Strong experience applying machine learning to physical systems
- Knowledge of digital twins, machine learning with digital twins, and sustainability applications
- Strong science or engineering background, including system-level analysis and modelling
- Sound understanding of machine-learning algorithms, data structures, and modern AI/ML platforms
- Ability to develop integrated software algorithms; work with large-scale computing, data-analysis, and modelling environments; and translate technical specifications into robust code
- Excellent research, development, written, and verbal communication skills in English
- Preferred: research publications in machine learning, applied statistics, or AI
- Preferred: experience designing, implementing, and operating AI/ML systems
- Preferred: experience with reinforcement learning, probabilistic time-series forecasting, optimisation, or control
- Preferred: experience with experimental systems, hardware-in-the-loop testing, or production software for research prototypes
Benefits
Comp & perks- Comprehensive suite of benefits supporting physical, financial, and emotional wellbeing
- Personal and professional development programs
- Flexible work and personal needs
- Inclusive workplace
- Reasonable accommodation during the application or interview process for applicants with disabilities