HPE Labs – AI/ML Research Scientist III

Hewlett Packard Enterprise • Milpitas, CA

2d • $136,500 - $276,500 • Onsite

About The Position

Hewlett Packard Enterprise (HPE) is seeking an AI/ML Research Scientist III for its HPE Labs division. This role is focused on original research and technical innovation in areas such as LLM reasoning and agents, reinforcement learning, generative diffusion models, and trustworthy AI. The scientist will conceive, design, and develop novel technologies to address significant challenges in areas like data center optimization, clean energy, and AI trustworthiness. The position also involves applied impact and prototyping, bridging research with deployment by building software prototypes and engineering solutions. Leadership, strategy, and collaboration are key, requiring technical thought leadership, contribution to research and product strategy, and collaboration with internal and external partners. Mentoring junior researchers is also part of the role.

Requirements

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

Nice To Haves

• 1-3 years of post-PhD research or industry experience preferred, but not required.
• Experience in research and development involving LLMs, and agentic AI platforms.
• Experience in research and development involving Reinforcement Learning and/or Digital Twins.
• Deep knowledge of different deep learning model architectures, uncertainty quantification, optimization, and control.
• Experience with generative models, including diffusion models and inverse models.
• Experience with ML model optimization, GPU acceleration, heterogeneous computation, system software, and performance optimization.

Responsibilities

• 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 challenges such as holistic data center co-optimization, 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.
• Build 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.
• 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 the team's collective expertise.

Benefits

• Comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
• Specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.
• Flexibility to manage our work and personal needs.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree