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This position was posted on April 6, 2026 and is likely no longer accepting applications. We've kept it here for historical reference. Check out the similar jobs below!

Pure Storage, Inc. logo

Applied AI Engineer

Job Overview

Location

Remote, United States

Job Type

Full-time

Category

Data Science

Date Posted

April 6, 2026

Full Job Description

📋 Description

  • As an Applied AI Engineer at Pure Storage, you will serve as a hybrid technical advisor and consultant, bridging deep AI expertise with business strategy to help enterprise customers turn AI ambitions into production outcomes on Pure’s platform.
  • Day to day, you will lead technical discovery and advisory engagements, advise on end-to-end AI deployment (model selection, training, inference optimization, data pipelines), collaborate cross-functionally to develop proof-of-value prototypes, create enablement content for field teams and partners, and represent Pure at conferences and with strategic technology partners.
  • You will join a small, global Applied AI team within Pure Storage, a leader in data storage innovation, working alongside Solutions, Marketing, Alliances, Engineering, Enablement, and Sales to shape AI strategy for Fortune 500 companies and contribute to thought leadership through publications and research.
  • In this role, you will deepen your impact as a T-shaped professional — combining deep technical roots in AI/ML systems with broad business acumen — while growing your influence in enterprise AI, publishing research, and advising C-suite leaders on ROI and strategy.

Skills & Technologies

Kubernetes
Kafka
PyTorch
Apache Spark
Data Science
Remote
Degree Required

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Pure Storage, Inc. logo
Pure Storage, Inc.
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About Pure Storage, Inc.

Pure Storage, Inc. is a Mountain View, California-based technology company that designs and manufactures all-flash storage arrays and data-management solutions for enterprise and cloud environments. Founded in 2009, it delivers NVMe storage, unified file-and-block platforms, and subscription services aimed at simplifying data operations and reducing total cost of ownership for large-scale workloads, databases, and analytics.

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