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Closed listing

HPE

Machine Learning Post Doctoral Research Scientist

Milpitas, CA, United States

$99,320 to $149,760 USD / year

This opening has closed.

The original listing is kept below for reference.

Find open jobs More jobs with this employer

About employer

Job details

Pay: $99,320 to $149,760 USD / year
Posting language: English
Posted: Nov 3, 2026

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Original job description

Archived listing. The details below describe a past opening.

Machine Learning Post Doctoral Research Scientist

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:

Role and Responsibilities

This Post Doctoral 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, fusion, 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 complex challenges such as nuclear fusion, supercomputing and data center sustainability, quantum computing acceleration, and the trustworthiness of AI/LLM-based systems. The role requires fast paced development of research in advanced agentic implementation involving Generative Diffusion Model, ML surrogates, Agentic LLMs, and Reinforcement Learning in it’s application to nuclear fusion.

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.

Qualifications and Education Requirements

PhD in Computer Science, Electrical Engineering, or related fields, focusing on Machine Learning for the dissertation.

Extensive experience with emerging Machine Learning techniques like diffusion models, LLMs, multi-agent systems, and Reinforcement Learning.

Experience in developing applications with deep learning frameworks like PyTorch, with a high level of software proficiency.

Preferred Skills

Experience in applying ML to nuclear fusion strongly preferred but not required.

Experience with Generative models is strongly preferred.

Experience and deep knowledge of different deep learning model architectures, uncertainty quantification, optimization, control, digital twins, and world models.

Strong programming skills in Python, data structures, and algorithms are required.

Experience with ML model optimization, GPU acceleration, heterogeneous computation, system software, and performance optimization is desired.

Accessibility

HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here.

Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.

What We Can Offer You:

Health & Wellbeing 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.

Personal & Professional Development 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.

Unconditional Inclusion 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.

Let's Stay Connected:

Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.

#unitedstates

#interns

Job:

AdministrationJob Level:

N/A "The expected salary/wage range for this position is provided below. Actual offer may vary from this range based upon geographic location, work experience, education/training, and/or skill level.

United States of America: Annual Salary USD 99,320 - 149,760 in California The listed salary range reflects base salary. Variable incentives may also be offered."

Information about employee benefits offered in the US can be found at https://myhperewards.com/main/new-hire-enrollment.html

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

Recruitment Fraud Alert

We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.

All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.

About employer

More about this job

Skills

Machine learning
Research
ML
Decision making
Leadership
Computer science
Electrical engineering
Deep learning
PyTorch
Python

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