Job description

Principal AI Research Scientist (HPE Labs) This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week 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: HPE Labs is seeking a Principal AI Research Scientist for the HPE Quantum team within Emergent Machine Intelligence, a senior individual-contributor role focused on original, publication-driven research in areas including foundation model reasoning, representation learning, physics-inspired machine learning, mechanistic interpretability, and interdisciplinary work at the intersection of AI, quantum computing, and physical science. The ideal candidate is intellectually broad, experimentally strong, and highly autonomous, with strong research judgment, a track record of publishing at leading AI venues, and the ability to identify impactful problems, develop original ideas collaboratively, and mentor junior researchers. . Key Responsibilities: Independently lead research projects from initial brainstorming and problem formulation through mathematical development, implementation, experimentation, analysis, and publication. Translate early-stage ideas into concrete hypotheses and design rapid, decisive experiments to determine whether a direction should be expanded, revised, or discontinued. Produce original research suitable for publication at leading venues such as NeurIPS, ICML, ICLR, and comparable conferences and journals. Maintain broad and current knowledge of modern AI research and use that knowledge to identify emerging opportunities, relevant prior work, and meaningful open problems. Collaborate with researchers, engineers, interns, and external partners across AI, physics, quantum computing, and advanced computing systems. Develop and release reusable research assets, including open-source software, models, experimental infrastructure, benchmarks, or datasets, when appropriate. Requirements: PhD in Computer Science, Artificial Intelligence, Machine Learning, Physics, Mathematics, or other related fields. Typically, 5 years experience Post PhD graduate studies. Strong and sustained record of original research in modern artificial intelligence or machine learning. Or equivalent. Demonstrated ability to convert research ideas into rigorous, complete, and publishable outcomes, with a strong publication record at leading machine-learning venues such as NeurIPS, ICML, and ICLR, or comparable peer-reviewed venues. Broad and current command of the AI and machine-learning literature, extending beyond a single model family, technique, or application area. Deep mathematical understanding of modern machine-learning methods, including their objectives, assumptions, optimization behavior, learning dynamics, and limitations. Excellent experimental skills, including hypothesis formulation, rapid prototyping, controlled evaluation, analysis of failure modes, and interpretation of results. Advanced proficiency in Python and PyTorch, with experience using common AI/ML packages, libraries, and research tooling. Experience working with research codebases, open-source libraries, HPC and distributed systems, and collaborative software-development practices. Strong software-engineering and algorithm implementation skills for research, including code design, version control, testing, debugging, profiling, performance optimization, and reproducible experimentation. Strong knowledge of state-of-the-art AI/ML algorithms and the engineering skills to adapt, implement, and apply them to real-world problems when needed. Strong written and verbal communication skills, with the ability to explain complex technical ideas, present research findings, and write high-quality scientific papers. Demonstrated ability to work autonomously and collaborate effectively in an interdisciplinary research environment. Desired Knowledge and Skills: Substantial research background in theoretical physics, statistical physics, quantum physics, condensed-matter physics, or another mathematically intensive area of physics, together with a proven research record in AI and machine learning. Research experience combining machine learning with physics, applied mathematics, dynamical systems, optimization, or scientific computing. Experience moving fluidly between mathematical formulation, algorithm development, implementation, and empirical validation. Working proficiency in C . Record of releasing high-quality open-source research software, models, benchmarks, datasets, or evaluation frameworks. Experience developing reusable experimental infrastructure or tools that accelerate research across multiple projects. Familiarity with neural quantum states, quantum many-body systems, quantum simulation, scientific machine learning, or other applications of AI to quantum science. Experience with advanced computational physics or chemistry methods, such as Monte Carlo simulations, density functional theory (DFT), molecular dynamics (MD), or related numerical methods. 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 #Hplabs Job: Engineering Job Level: TCP_05 "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 172,000 - 328,000 in Massachusetts // 172,000 - 349,000 in California // 152,000 - 349,000 in Texas 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 myhperewards.com 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.

Requirements

Must-haves

Principal AI Research Scientist (HPE Labs)
This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office.
Independently lead research projects from initial brainstorming and problem formulation through mathematical development, implementation, experimentation, analysis, and publication.
Translate early-stage ideas into concrete hypotheses and design rapid, decisive experiments to determine whether a direction should be expanded, revised, or discontinued.
Produce original research suitable for publication at leading venues such as NeurIPS, ICML, ICLR, and comparable conferences and journals.
Maintain broad and current knowledge of modern AI research and use that knowledge to identify emerging opportunities, relevant prior work, and meaningful open problems.
Collaborate with researchers, engineers, interns, and external partners across AI, physics, quantum computing, and advanced computing systems.
Develop and release reusable research assets, including open-source software, models, experimental infrastructure, benchmarks, or datasets, when appropriate.
PhD in Computer Science, Artificial Intelligence, Machine Learning, Physics, Mathematics, or other related fields.
Typically, 5 years experience Post PhD graduate studies. Strong and sustained record of original research in modern artificial intelligence or machine learning. Or equivalent.
Broad and current command of the AI and machine-learning literature, extending beyond a single model family, technique, or application area.
Deep mathematical understanding of modern machine-learning methods, including their objectives, assumptions, optimization behavior, learning dynamics, and limitations.
Excellent experimental skills, including hypothesis formulation, rapid prototyping, controlled evaluation, analysis of failure modes, and interpretation of results.
Advanced proficiency in Python and PyTorch, with experience using common AI/ML packages, libraries, and research tooling.
Experience working with research codebases, open-source libraries, HPC and distributed systems, and collaborative software-development practices.
Strong software-engineering and algorithm implementation skills for research, including code design, version control, testing, debugging, profiling, performance optimization, and reproducible experimentation.
Strong knowledge of state-of-the-art AI/ML algorithms and the engineering skills to adapt, implement, and apply them to real-world problems when needed.
Strong written and verbal communication skills, with the ability to explain complex technical ideas, present research findings, and write high-quality scientific papers.
Demonstrated ability to work autonomously and collaborate effectively in an interdisciplinary research environment.
Research experience combining machine learning with physics, applied mathematics, dynamical systems, optimization, or scientific computing.
Experience moving fluidly between mathematical formulation, algorithm development, implementation, and empirical validation.
Working proficiency in C .
Record of releasing high-quality open-source research software, models, benchmarks, datasets, or evaluation frameworks.
Experience developing reusable experimental infrastructure or tools that accelerate research across multiple projects.

Nice-to-haves

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Application prep

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Keywords to mirror

aimachine learningpythonml

Platform: workday
Effort: long

Benefits

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Vision

Professional Development