Job description

AI Data Foundation Research Engineer 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 Successful candidates will work on development of infrastructures and algorithms to capture, manage, enhance and interpret meta-data and lineage for AI pipelines to enable reproducibility, reuse and optimization of pipelines; search, discovery, selection and usage of relevant high quality data for trustworthy AI outcomes across multiple AI applications; development, evaluation and testing of Foundation AI models for different modalities: Natural Language Processing - NLP, Large Language Models - LLM, Time Series Analysis, Computer Vision, etc., and augmentation of AI models with structured knowledge (i.e., knowledge infused learning)., including data and knowledge context retrieval, filtering, prioritization, advanced reasoning, reasoning trace capture and validation, to improve quality of AI agentic workflows. Successful candidates will also work on development of Agentic OS infrastructures to enable consistent management of context, reasoning, governance policies and guardrails across different agentic harnesses. We are particularly interested in individuals with a background in computer systems, machine learning, deep learning, statistics, generative AI, data management, and big data pipelines, with good understanding of the current state of the art, major trends and opportunities, and a demonstrated track record in innovative research. The ideal candidate can thrive in an applied research environment, balancing significant technical contributions published externally in open source with the hands-on engineering skill to bring such contributions to practice in partnering with our internal software development teams and external partners. Qualifications and Education Requirements PhD in Computer Science or related fields with a focus on data engineering and data science, in particular Machine Learning, Deep Learning, and/or data management for AI plus 3 years of relevant industry experience. Preferred Skills Research experience in Generative AI, Deep Learning and Machine Learning Experience with advanced AI model architectures: LLMs, Time Series Foundation Models, Diffusion Models, etc. Expertise with end-to-end pipelines for AI and Machine Learning and in particular the data layer underlying the pipelines (e.g., DVC, lakeFS, Pachyderm, Common Metadata Framework, Flowcept) Experience in AI model development lifecycle, ML/deep learning frameworks and MLOps platforms (e.g. Pytorch/Tensorflow, MLFlow, Kubeflow, Ray) Experience with agentic AI platforms (e.g., LangGraph, CrewAI, ADK, Autogen, LlamaIndex, OpenCode, Cloud Code, Academy, etc.) Outstanding analytical and problem solving skills Strong programming skills in Python with high proficiency in data structures and algorithms Proficiency in using coding agents and co-pilots for accelerated code development Experience with CI/CD code development Experience in containerized development and orchestration tools (e.g. Kubernetes, Ezmeral) Experience with knowledge graphs and knowledge infused learning – a plus Expertise in research of data and workflow management systems – a plus Experience with hybrid AI-HPC workflows (e.g., AI surrogate modeling, computational steering of experiments and/or HPC simulations) – a plus Experience in system software performance and scalability optimization – a plus Experience with multi-threaded programming, parallel processing, OOD/OOP/distributed programming – a plus 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 Job: Engineering Job Level: TCP_03 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 132,500 - 252,500 in Colorado 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 The estimated job application period closure is November 30 2026; this timeline is provided for transparency and internal planning purposes. 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

AI Data Foundation Research Engineer
Experience with advanced AI model architectures: LLMs, Time Series Foundation Models, Diffusion Models, etc.
Expertise with end-to-end pipelines for AI and Machine Learning and in particular the data layer underlying the pipelines (e.g., DVC, lakeFS, Pachyderm, Common Metadata Framework, Flowcept)
Experience in AI model development lifecycle, ML/deep learning frameworks and MLOps platforms (e.g. Pytorch/Tensorflow, MLFlow, Kubeflow, Ray)
Experience with agentic AI platforms (e.g., LangGraph, CrewAI, ADK, Autogen, LlamaIndex, OpenCode, Cloud Code, Academy, etc.)
Outstanding analytical and problem solving skills
Strong programming skills in Python with high proficiency in data structures and algorithms
Proficiency in using coding agents and co-pilots for accelerated code development
Experience with CI/CD code development
Experience in containerized development and orchestration tools (e.g. Kubernetes, Ezmeral)
Accessibility
Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.
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
Unconditional Inclusion
Follow HPECareers on Instagram to see the latest on people, culture and tech at HPE.
#unitedstates

Nice-to-haves

Preferred Skills Research experience in Generative AI, Deep Learning and Machine Learning
Experience with knowledge graphs and knowledge infused learning – a plus
Expertise in research of data and workflow management systems – a plus
Experience with hybrid AI-HPC workflows (e.g., AI surrogate modeling, computational steering of experiments and/or HPC simulations) – a plus
Experience in system software performance and scalability optimization – a plus
Experience with multi-threaded programming, parallel processing, OOD/OOP/distributed programming – a plus

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aillmmachine learningmlpythonci/cdkubernetesaccessibility

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Vision

Professional Development