About the role
HPE Labs – AI/ML Research Scientist III This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE office.
Who We Are: Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE. Job Description: Hewlett Packard Labs, the central research organization of Hewlett Packard Enterprise, is seeking an AI/ML Research Scientist to join its core Machine Learning research team based in the San Francisco Bay Area. This team has an established track record of foundational contributions spanning reinforcement learning for complex systems, large language models and reasoning, agentic AI, digital twins, trustworthy AI, generative models, optimization, and tokenomics, with award-winning top-tier publications. This role offers a rare opportunity to operate at the intersection of frontier AI research and high-impact, real-world applications such as sustainability of data centers, fusion energy, wave energy, and optimization of AI inference workloads and quantum computing. You will work alongside world-class researchers and collaborators, publish at premier venues, and directly influence HPE's research direction and product strategy. The position demands both scientific rigor and engineering excellence: you will move from theory to prototype at a rapid pace. Role and
Responsibilities: Original Research and Technical Innovation Conduct original research in areas including LLM reasoning and agents, reinforcement learning, agentic and multi-agent systems, generative diffusion models, inverse models, digital twins, trustworthy AI, tokenomics, optimization, and uncertainty quantification. Conceive, design, and develop novel technologies addressing some of the most consequential challenges of our time, such as holistic data center co-optimization (computation, energy, water resources, power systems, waste heat recovery), nuclear fusion energy, AI-driven acceleration of AI workloads and quantum computing simulation on HPC systems, and trustworthiness of AI/LLM-based systems. Develop novel methods for high-assurance multi-agent and multi-objective real-time control of complex cyber-physical systems, LLM-enabled explainable decision-making , agentic frameworks, and diffusion-model and inverse-model approaches for design and optimization. Publish at leading venues (e.g., NeurIPS, ICML, ICLR, AAAI) and develop patent disclosures that strengthen HPE's intellectual property portfolio. Applied Impact and Prototyping Bridge the gap between research and deployment by building robust software prototypes and engineering solutions that address use cases across domains such as data center and private cloud optimization, clean energy systems, and large-scale scientific computing. Architect and implement systems involving GPU acceleration, heterogeneous computation, model optimization, and real-time data and streaming workflows to deliver AI capabilities at scale and under operational constraints. Leadership, Strategy and Collaboration Provide technical thought leadership within the core ML research team and across HPE by identifying, evaluating, and shaping emerging technology opportunities in AI and machine learning. Contribute to HPE's research and product strategy by translating research insights into actionable technical roadmaps and by articulating the significance and potential of new directions to both technical and executive audiences. Collaborate closely with internal research teams, engineering organizations, and business units across HPE to ensure research outcomes align with strategic priorities and create measurable value. Engage with external partners, including academic institutions, national laboratories, and industry collaborators, to amplify research impact and maintain visibility within the broader research community. Mentor junior researchers and contribute to the growth and development of
