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WekaIO

AI-native data platform for high-performance workloads

Senior Technical Alliance Engineer - AI Platform

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeCampbell, CA, USA$185k - $215kIn-person

About the Job

Requirements

  • Strong understanding of parallel file systems, including Lustre, IBM Spectrum Scale, WekaFS, and BeeGFS.
  • Expertise in storage benchmarking tools, including FIO, IOzone, mdtest, IOR, Elbencho, and SPECStorage.
  • Hands-on experience with infrastructure setup and configuration, and strong knowledge of NVMe storage and its role in high-performance computing and AI/ML workloads.
  • Solid grasp of AI/ML workflows and their interaction with storage architectures.
  • Experience working with NVIDIA GPU architectures, GPUDirect Storage, and Spectrum-X networking.
  • Deep knowledge of file system internals, storage networking, and data management technologies.
  • Experience working in a storage lab environment, setting up test environments, and troubleshooting performance issues.
  • Ability to create technical content and presentations for technical and business audiences.
  • Ability to convey complex technical concepts in an understandable way.
  • Strong knowledge of virtualization and containerization technologies.

Responsibilities

  • Work with alliance partners to explore product integration opportunities that jointly solve customer problems.
  • Work on partner certification and validation.
  • Develop and execute benchmarking methodologies to measure and showcase parallel file system performance, focusing on use-case-based benchmarks that highlight product differentiation.
  • Work hands-on with NVMe storage, AI/ML workloads, and high-performance file systems to optimize performance and validate use cases.
  • Use NVIDIA technologies, including GPUDirect Storage, GPU architectures, Spectrum-X networking, and accelerator architectures, to enhance storage performance and AI/ML workloads.
  • Create technical content, including whitepapers, blogs, presentations, and solution briefs, to communicate the value of the technology.
  • Collaborate with engineering teams to provide feedback on product features and performance tuning.
  • Engage with customers and partners through technical presentations, webinars, and hands-on workshops.
  • Evaluate partner product features and replicate customer scenarios.
  • Support field teams with technical insights and assistance in pre-sales engagements.
  • Analyze market trends in storage, NVMe, AI/ML workloads, and GPU-accelerated computing to refine messaging and competitive positioning.

Desired Qualifications

  • Experience with containerized and cloud storage architectures.
  • Familiarity with RDMA, InfiniBand, RoCE, and high-speed networking.
  • Prior experience as a TME, Solutions Architect, or Storage Performance Engineer in a storage-focused company.
  • Hands-on experience with Kubernetes.

About the Company

WekaIO

AI-native data platform for high-performance workloads

WEKA is an AI-native data platform that provides a cloud- and hardware-agnostic software solution for performance-heavy AI, ML, and GPU workloads. The WEKA Data Platform organizes and speeds data across on-premises, cloud, edge, and hybrid environments to turn isolated data into dynamic pipelines. It delivers high throughput and scalable data management to support enterprise AI initiatives and research workloads, helping teams gain faster insights. WEKA differentiates itself with a single scalable platform that works across multiple infrastructure footprints and emphasizes energy efficiency, aiming to simplify and accelerate data-driven AI workflows for large enterprises and research groups while replacing legacy data silos.

Company size
501-1,000
Company stage
Series E
Total funding
$465.1M
Headquarters
Campbell, CA
Founded
2013

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