AI Data Foundation Research Engineer
Hewlett Packard Enterprise | HPE
- Location
- Fort Collins, CO, US
- Track
- AI Researcher
- Salary
- $133K–$253K / yr
- Posted
- October 5, 2026
- Last checked
- October 6, 2026
- Source
- Indeed
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.
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