HPE Labs – AI/ML Research Scientist III

Hewlett Packard Enterprise • Milpitas, CA

3d • $136,500 - $276,500 • Onsite

About The Position

Hewlett Packard Enterprise (HPE) is a global edge-to-cloud company dedicated to advancing how people live and work. We empower companies to connect, protect, analyze, and act on their data and applications, regardless of location, from the edge to the cloud. Our culture encourages innovation, values diverse backgrounds, and offers flexibility to balance work and personal needs. We are committed to making bold moves together and being a force for good, providing opportunities for career growth and development.

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.
• 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 (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 research at leading venues (e.g., NeurIPS, ICML, ICLR, AAAI) and develop patent disclosures.
• Build robust software prototypes and engineering solutions for use cases in 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.
• 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.
• Collaborate closely with internal research teams, engineering organizations, and business units across HPE.
• Engage with external partners, including academic institutions, national laboratories, and industry collaborators.
• 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