Pioneer AI Data Foundation Engineer (Research)

Hewlett Packard Enterprise Development LP; Northern (KY); Hybrid; USD 133,000 - 253,000; Full time

Job summary

Hewlett Packard Enterprise is seeking an AI Data Foundation Research Engineer to advance metadata, lineage and data management for AI pipelines. You will explore reproducibility, data quality, and scalable AI model evaluation across NLP, LLMs, time series and computer vision domains.

The role emphasizes research-driven contributions with practical engineering impact, collaborating with internal software teams and partners on evolving infrastructure and knowledge-infused learning approaches.

Qualifications

• PhD in Computer Science or related field with data engineering/ML focus.
• 3+ years of relevant industry experience in AI/data infrastructure.
• Strong publication track record and hands-on research experience.

Responsibilities

• Develop infrastructures and algorithms to capture, manage, and interpret meta-data and lineage for AI pipelines.
• Enable reproducibility, reuse and optimization of AI pipelines across modalities.
• Contribute to evaluation and testing of Foundation AI models (NLP/LLM/Time Series/ Vision).
• Build agentic OS infrastructures for context, governance, and guardrails across harnesses.

Skills

Generative AI

Deep Learning

Machine Learning

Python programming

Data engineering

Research experience

Education

PhD in Computer Science or related field

Tools

DVC

lakeFS

Pachyderm

Common Metadata Framework

Flowcept

MLFlow

Kubeflow

Ray

LangGraph

CrewAI

ADK

LlamaIndex

OpenCode

Cloud Code

Academy

Job description

Hewlett Packard Enterprise is seeking an AI Data Foundation Research Engineer to advance metadata, lineage and data management for AI pipelines. You will explore reproducibility, data quality, and scalable AI model evaluation across NLP, LLMs, time series and computer vision domains.

The role emphasizes research-driven contributions with practical engineering impact, collaborating with internal software teams and partners on evolving infrastructure and knowledge-infused learning approaches.