AI Data Foundation Research Engineer

Company: HPE
Location: Fort Collins, CO
Schedule: Full-time
Work Model: Hybrid (2 days per week in office)

Who We Are:

Hewlett Packard Enterprise is a global edge-to-cloud company that helps organizations connect, protect, analyze, and act on their data and applications. Our culture values varied backgrounds and supports career growth.

Job Description:

The successful candidate will develop methods for context discovery, retrieval, filtering, prioritization, multi-modal data representation, advanced reasoning, tool calling, and reasoning trace validation in AI workflows. Responsibilities include:

Development of capture, management, search, enhancement, and interpretation of metadata and lineage for AI pipelines.
Discovery and usage of high-quality data for trustworthy AI outcomes across multiple applications.
Development, evaluation, and testing of Foundation AI models for various modalities including NLP, LLM, Time Series Analysis, and Computer Vision.
Augmentation of AI models with structured knowledge.
Collaboration with internal software development teams and external partners.

Must-have Requirements:

PhD in Computer Science or related fields with a focus on data engineering and data science, plus 3 years of relevant industry experience.
Research experience in Generative AI, Deep Learning, and Machine Learning.
Experience with advanced AI model architectures such as LLMs and Time Series Foundation Models.
Expertise with end-to-end AI and Machine Learning pipelines.
Experience in AI model development lifecycle and MLOps platforms.
Experience with agentic AI platforms.

Preferred Skills:

Strong programming skills in Python; proficiency in C/C++.
Experience with CI/CD code development.
Outstanding analytical and problem-solving skills.
Experience with hybrid AI-HPC workflows.
Knowledge of knowledge graphs and knowledge infused learning.
Experience in system software performance optimization.
Experience with multi-threaded programming and containerized development tools.

Benefits:

Comprehensive health and wellbeing benefits.
Personal and professional development programs.
Variable incentives may also be offered.