1 week ago

AI Processing in Electronic Control Unit

Inalfa Roof Systems Group

Venray

1 week ago

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Inalfa Roof Systems is seeking an intern to investigate edge AI processing in electronic control units (ECUs) for roof systems. The candidate will participate in the design, deployment, testing, and optimization of AI algorithms and lightweight neural networks on automotive ECUs. This is a full-time, on-site internship in Venray, Netherlands, requiring familiarity with C/C++, Python, and deep learning frameworks.

Core AIOn-siteFull-timeInternshipC/C++Python

AI Processing in Electronic Control Unit

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Core AIOn-siteFull-timeInternshipC/C++

Salary

Not specified

Work Location

Venray, Limburg, Netherlands, NL

Work Model

On-site

Employment Type

Full-time

Experience Level

Internship

Contract Length

3 months

Core Qualifications

Technical (Must-have)

C/C++PythonPyTorchTensorFlowONNX

Soft Skills

Quick learning abilityRigorous work attitudeTeam communicationExecution skills

Preferred Qualifications

Technical (Nice-to-have)

Model lightweightQuantizationModel deployment on edge devicesAutomotive ECUAutomotive softwareAutomotive bus protocol

Key Responsibilities

•Search the possible solutions like MCU with neural processing unit(NPU) to accommodate AI processing to resolve the actual engineering problems.
•Implementing existing feature(s) as part of the NPU (e.g. Thermal protection of motor, or Anti-Pinch)
•Feature enhancement (any feature which is easy for NPU but difficult for the traditional SW, such as wear-out estimation of the motor, ...)
•Support AI algorithm pre-processing, post-processing, data sorting and annotation for ECU application scenarios.
•Conduct performance testing, latency analysis, resource occupancy (RAM/ROM/CPU) evaluation of AI models running on ECUs, and put forward optimization suggestions.
•Complete other technical tasks assigned by supervisors related to ECU AI processing development.

AIECUAutomotiveInternshipEdge AINeural NetworksEmbedded Systems

Key Responsibilities

•Search the possible solutions like MCU with neural processing unit(NPU) to accommodate AI processing to resolve the actual engineering problems.

•Implementing existing feature(s) as part of the NPU (e.g. Thermal protection of motor, or Anti-Pinch)

•Feature enhancement (any feature which is easy for NPU but difficult for the traditional SW, such as wear-out estimation of the motor, ...)

•Support AI algorithm pre-processing, post-processing, data sorting and annotation for ECU application scenarios.

•Conduct performance testing, latency analysis, resource occupancy (RAM/ROM/CPU) evaluation of AI models running on ECUs, and put forward optimization suggestions.

•Complete other technical tasks assigned by supervisors related to ECU AI processing development.