AI Platform Support Engineer

Cynet Systems•Austin, TX

1d•Onsite

About The Position

The Support Specialist will provide technical support and issue resolution for AI platforms across Windows and Linux operating systems. This role serves as a key interface between customers, field engineering teams, software developers, and hardware engineering organizations to diagnose and resolve platform, driver, AI framework, and application issues. The ideal candidate will have experience supporting x86 platforms, AI/ML software environments, GPU computing technologies, and operating system-level debugging. This position requires strong troubleshooting skills spanning hardware, firmware, drivers, operating systems, and the AI software ecosystem, including ROCm.

Requirements

3+ years of technical support, system validation, or software support experience.
Strong knowledge of Windows, Linux, and x86 platform architecture.
Experience with Python, Bash, or PowerShell scripting.
Excellent troubleshooting and communication skills.

Nice To Haves

Experience with ROCm, GPU/NPU compute, and AI/ML frameworks.
Familiarity with PyTorch, TensorFlow, Docker, and AI model deployment.
Knowledge of BIOS/UEFI, device drivers, and performance analysis tools.

Responsibilities

Serve as the primary technical contact for reported platform issues.
Analyze and resolve hardware, software, BIOS, driver, and application-related issues.
Monitor inbox/ticket system and reproduce reported defects in internal lab environments.
Manage support cases through closure while maintaining high customer satisfaction.
Provide technical guidance on platform configuration, performance tuning, and best practices.
Generate weekly reports.
Develop collateral about common issues and issue trends.
Support systems running Microsoft Windows and Linux distributions (RexOS, Debian, Ubuntu etc.).
Troubleshoot platform-level issues involving CPU, Integrated GPU, and NPU (Neural Processing Unit).
Manage issues related to the memory subsystem, power and thermal management, and BIOS/UEFI.
Support deployment and optimization of AI workloads on platforms.
Assist with AI software ecosystem setup and validation.
Troubleshoot issues involving ROCm, PyTorch, Hugging Face models, and AI Software.
Analyze workload compatibility, model execution failures, and performance bottlenecks.
Collect and analyze logs, traces, dumps, and telemetry data.
Perform issue isolation across hardware, firmware, drivers, operating systems, and AI frameworks.
Identify root causes and work with engineering teams to deliver fixes.
Escalate product defects with clear technical documentation and reproducible test cases.