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Hewlett Packard Enterprise

Builds servers, networking and private cloud

AI/ML Research Scientist 3

AI ResearchConfirmed live in the last 24 hours
Full-timeMilpitas, CA, USA

About the Job

Requirements

  • A PhD in Computer Science, Electrical Engineering, or a related field is required, with a dissertation focus on Machine Learning.
  • Extensive research experience with Large Language Models and Reinforcement Learning is required.
  • Experience developing applications with deep learning frameworks such as PyTorch, with a high level of software proficiency, is required.
  • Strong programming skills in Python, including proficiency with data structures and algorithms, are required.

Responsibilities

  • Conduct original research in 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 data center co-optimization across computation, energy, water resources, power systems, and 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 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 such as NeurIPS, ICML, ICLR, and AAAI, and develop patent disclosures that strengthen HPE's intellectual property portfolio.
  • Build robust software prototypes and engineering solutions that bridge research and deployment for 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.
  • Provide technical thought leadership within the core machine learning 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 communicating the significance and potential of new directions to technical and executive audiences.
  • Collaborate with internal research teams, engineering organizations, and business units across HPE to align research outcomes 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 the team's collective expertise.

Desired Qualifications

  • One to three years of post-PhD research or industry experience is preferred but not required.
  • Experience in research and development involving LLMs and agentic AI platforms is preferred.
  • Experience in research and development involving reinforcement learning and/or digital twins is preferred.
  • Deep knowledge of deep learning model architectures, uncertainty quantification, optimization, and control is preferred.
  • Experience with generative models, including diffusion models and inverse models, is preferred.
  • Experience with machine learning model optimization, GPU acceleration, heterogeneous computation, system software, and performance optimization is preferred.

About the Company

Hewlett Packard Enterprise

Builds servers, networking and private cloud

Hewlett Packard Enterprise sells servers, storage, networking and hybrid cloud software to large companies, governments and service providers. Its GreenLake platform lets customers run on-premises hardware as a metered cloud service, and its Cray supercomputers run national lab and AI training workloads. The networking business, built on Aruba and Juniper Networks, supplies campus, data-center and routing equipment. Revenue comes from hardware sales, multiyear support contracts, financing and subscriptions. The company traces its roots to Hewlett-Packard, founded in 1939, became a separate public company in 2015 and is headquartered in Houston, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Houston, TX
Founded
1939

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