Machine Learning and LLM Research Scientist

Hewlett Packard Enterprise • Spring, TX

2d • Onsite

About The Position

This Research Scientist role sits within the core Machine Learning research team at Hewlett Packard Labs, HPE’s primary research organization, based in the San Francisco Bay Area. The team is recognized for award-winning, top-tier publications and foundational contributions spanning reinforcement learning for complex systems, large language models (LLMs), agentic AI, generative diffusion models, trustworthy AI, optimization, and digital twins. As part of this team, you will bridge frontier research with real-world impact, tackling challenges such as supercomputing and data center sustainability, nuclear fusion, and the trustworthiness of AI/LLM-based systems. You will conduct original research and develop novel technologies across areas, including LLM reasoning, agentic and multi-agent systems, reinforcement learning, generative modeling, digital twins, clean energy, and data center/private cloud optimization. The work includes multi-agent and multi-objective real-time control of complex physical systems, LLM-enabled explainable decision-making, agentic frameworks for cyber-physical systems, analytics and uncertainty quantification, and diffusion-model approaches for design and optimization. You will be expected to provide technical thought leadership, collaborate closely with internal teams and external partners, and contribute to HPE’s research and product strategy by identifying and shaping emerging technology opportunities. Success in this role includes publishing at leading venues (e.g., NeurIPS, ICML, AAAI) and developing patent disclosures. The position is highly hands-on, involving software prototyping and engineering, GPU acceleration, model optimization, and real-time data/streaming workflows to deliver robust AI capabilities for production-relevant use cases. This is a rare opportunity to operate at the intersection of AI research and high-impact applications with world-class collaborators. This is an office-based role and the selected candidate will be working from HPE office in Spring, TX.

Requirements

• PhD in Computer Science, Electrical Engineering, or related fields, focusing on Machine Learning for the dissertation.
• Extensive experience with Large Language Models, Agentic AI, and Reinforcement Learning.
• Experience in developing applications with deep learning frameworks like PyTorch, with a high level of software proficiency.

Nice To Haves

• 1-3 years of experience preferred, but not required.
• Experience in research and development in the refinements of Large Language Models and Agentic Framework.
• Experience in research and development in Reinforcement Learning and/or Digital Twins.
• Experience and deep knowledge of different deep learning model architectures, uncertainty quantification, optimization, and control.
• Strong programming skills in Python, data structures, and algorithms are required.
• Experience with Generative models is desired.
• Experience with ML model optimization, GPU acceleration, heterogeneous computation, system software, and performance optimization is desired.
• Experience in Python Web Frameworks – Django, Flask - a plus but not required.

Responsibilities

• Conduct original research and develop novel technologies across areas, including LLM reasoning, agentic and multi-agent systems, reinforcement learning, generative modeling, digital twins, clean energy, and data center/private cloud optimization.
• Provide technical thought leadership, collaborate closely with internal teams and external partners, and contribute to HPE’s research and product strategy by identifying and shaping emerging technology opportunities.
• Publish at leading venues (e.g., NeurIPS, ICML, AAAI) and developing patent disclosures.
• Software prototyping and engineering, GPU acceleration, model optimization, and real-time data/streaming workflows to deliver robust AI capabilities for production-relevant use cases.

Benefits

• We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
• We also invest in your career because the better you are, the better we all are. We have 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.
• We are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees