Educational qualification:
- Undergraduation in relevant engineering stream
Experience :
- At least 3 years in the area of IVN development with deliveries in CAN 2.0, CAN-FD and optionally in Ethernet protocols
Mandatory/required Skills :
- Expertise in working with legacy and new-age automotive IVN protocols - CAN 2.0, CAN-FD, FlexRay, Ethernet.
- Awareness of upcoming IVN architectures, protocols and toolchains.
- Benchmark vehicle networks with limited information on their E/E architecture to identify sensor and actuator signals from monitoring the vehicle bus.
- Use BGSW-approved GenAI coding aids (with the awareness of the data with the maximum allowed security classes).
- Ideate and communicate with aids (such as draw.io) the in-vehicle networking architecture for xDomain topics on a given vehicle.
- Analyse and objectively present trade-offs of different networking architectures for various E/E architectures (distributed, fusion, centralised, etc.).
- CAPL scripting for Vector solutions, equivalent for Intrepid's solutions, Py-CAN for working with rapid prototyping using R-Pi/Arduino and their respective HAT equivalents.
Preferred Skills :
- Ability to architect and interface automotive IVN with non-mobility electronics interfaces utilising intermediaries such as SOME/IP messages