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AI Platform Applications Engineer – Principal
Company | d-Matrix |
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Location | Santa Clara, CA, USA |
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Salary | $161000 – $260000 |
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Type | Full-Time |
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Degrees | Bachelor’s |
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Experience Level | Expert or higher |
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Requirements
- BS Engineering degree in Electrical Engineering, Computer Engineering, or Computer Science with 15+ years of relevant experience in customer engineering and field support for enterprise datacenter products
- Hands on experience with x86 server bring up and deployment with hardware accelerators
- Have strong analytical skills and past experience in reviewing enterprise system design
- Professional-level interpersonal skills, including ability to adjust your communication to the technical level of the audience.
Responsibilities
- Provide customer support, including but not limited to guiding customers through the process of using tools and/or platforms, timely and accurate responses to customer queries, root cause analysis of customer issues, reproducing & resolving the same, escalating unresolved issues and providing timely workarounds.
- Perform system design reviews for data center applications to ensure partner designs meet our guidelines.
- Work with OEM and ODM partners on system integration related to thermal, mechanical, electrical, PCIe and/or other interconnect interfaces including out-of-band management services.
- Understand system design and datacenter infrastructure requirements for AI workloads, develop reference configurations and technical guides.
- Conduct the installation, configuration and bring-up of server hardware. Perform functional and performance validation testing.
- Create product specifications, hardware design guides, application notes, and other supporting technical collateral.
Preferred Qualifications
- Hands-on understanding of AI/ML infrastructure and hardware accelerators
- Automation Experience with Linux or Windows shell scripting, Python or Go
- Outstanding communication and presentation skills
- Experience with leading AI/ML frameworks such as PyTorch, TensorFlow, ONNX, etc. and container orchestration platforms such as Kubernetes