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Hewlett Packard Enterprise

Builds servers, networking and private cloud

AI Data Foundation Research Engineer

AI ResearchConfirmed live in the last 24 hours
Full-timeFort Collins, CO, USA

About the Job

Requirements

  • A PhD in Computer Science or a related field, focused on data engineering and data science, particularly machine learning, deep learning, and/or data management for AI.
  • At least three years of relevant industry experience.
  • A background in computer systems, machine learning, deep learning, statistics, generative AI, data management, and big data pipelines, with understanding of the state of the art, trends, and opportunities, and a demonstrated record of innovative research.
  • Ability to balance externally published technical contributions, including open-source contributions, with hands-on engineering and collaboration with internal software development teams and external partners.

Responsibilities

  • Develop infrastructures and algorithms to capture, manage, enhance, and interpret metadata and lineage for AI pipelines, enabling reproducibility, reuse, and pipeline optimization.
  • Develop search, discovery, selection, and usage capabilities for relevant high-quality data to support trustworthy AI outcomes across multiple AI applications.
  • Develop, evaluate, and test foundation AI models for different modalities, including natural language processing, large language models, time series analysis, and computer vision.
  • Augment AI models with structured knowledge through knowledge-infused learning, including data and knowledge context retrieval, filtering, prioritization, advanced reasoning, reasoning-trace capture, and validation to improve AI agentic workflows.
  • Develop Agentic OS infrastructures to consistently manage context, reasoning, governance policies, and guardrails across different agentic harnesses.

Desired Qualifications

  • Research experience in generative AI, deep learning, and machine learning.
  • Experience with advanced AI model architectures, including large language models, time series foundation models, and diffusion models.
  • Experience with end-to-end AI and machine learning pipelines, particularly their data layer, using tools such as DVC, lakeFS, Pachyderm, Common Metadata Framework, or Flowcept.
  • Experience with AI model development lifecycles, machine learning and deep learning frameworks, and MLOps platforms such as PyTorch, TensorFlow, MLflow, Kubeflow, or Ray.
  • Experience with agentic AI platforms such as LangGraph, CrewAI, ADK, AutoGen, LlamaIndex, OpenCode, Cloud Code, or Academy.
  • Strong analytical and problem-solving skills.
  • Strong programming skills in Python, including high proficiency in data structures and algorithms.
  • Proficiency using coding agents and copilots to accelerate code development.
  • Experience with CI/CD code development.
  • Experience with containerized development and orchestration tools such as Kubernetes and Ezmeral.
  • Experience with knowledge graphs and knowledge-infused learning.
  • Research expertise in data and workflow management systems.
  • Experience with hybrid AI-HPC workflows, such as AI surrogate modeling, computational steering of experiments, or HPC simulations.
  • Experience with system software performance and scalability optimization.
  • Experience with multithreaded programming, parallel processing, object-oriented design and programming, and distributed programming.

About the Company

Hewlett Packard Enterprise

Builds servers, networking and private cloud

Hewlett Packard Enterprise sells servers, storage, networking and hybrid cloud software to large companies, governments and service providers. Its GreenLake platform lets customers run on-premises hardware as a metered cloud service, and its Cray supercomputers run national lab and AI training workloads. The networking business, built on Aruba and Juniper Networks, supplies campus, data-center and routing equipment. Revenue comes from hardware sales, multiyear support contracts, financing and subscriptions. The company traces its roots to Hewlett-Packard, founded in 1939, became a separate public company in 2015 and is headquartered in Houston, Texas.

Company size
10,001+
Company stage
IPO
Headquarters
Houston, TX
Founded
1939

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