2 days ago

System Engineer (Token Factory)

Jobgether

Netherlands

2 days ago

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System Engineer needed for a partner company's AI infrastructure team, building large-scale inference platforms. The role involves low-level kernel development, GPU optimization, and performance tuning. Requires strong C++ or GPU programming skills and experience with profiling tools.

AIRemoteFull-timeEntry LevelC++GPU Programming

System Engineer (Token Factory)

Apply

AIRemoteFull-timeEntry LevelC++

Salary

Not specified

Work Location

Netherlands, NL

Work Model

Fully remote working flexibility within Europe.

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)

C++GPU programmingCUDAROCmCUTLASSTritonPallasMosaic GPUprofilingdebuggingCPU architectureGPU architecturememory hierarchyLinux internalscompiler toolchains

Soft Skills

problem-solvingtechnical curiositycollaboration

Preferred Qualifications

Technical (Nice-to-have)

TensorRTTVMperfVTuneNsightROCm profilermachine learning inference runtimesAI deployment frameworks

Key Responsibilities

•Develop and optimize low-level kernels, runtime components, and system software for high-performance AI inference workloads.
•Improve inference engine performance across GPU platforms by identifying bottlenecks and implementing advanced optimization techniques.
•Profile, debug, and resolve system-level and hardware-level performance issues across CPU and GPU environments.
•Integrate support for emerging GPU architectures and next-generation hardware platforms.
•Collaborate closely with machine learning and backend engineering teams to optimize end-to-end execution pipelines.
•Contribute to the continuous improvement of large-scale AI infrastructure through technical innovation, performance analysis, and system-level problem solving.

System EngineerAI infrastructureGPU computingC++CUDAROCmperformance optimizationremoteNetherlandsfull-time

Key Responsibilities

•Develop and optimize low-level kernels, runtime components, and system software for high-performance AI inference workloads.

•Improve inference engine performance across GPU platforms by identifying bottlenecks and implementing advanced optimization techniques.

•Profile, debug, and resolve system-level and hardware-level performance issues across CPU and GPU environments.

•Integrate support for emerging GPU architectures and next-generation hardware platforms.

•Collaborate closely with machine learning and backend engineering teams to optimize end-to-end execution pipelines.

•Contribute to the continuous improvement of large-scale AI infrastructure through technical innovation, performance analysis, and system-level problem solving.