Advanced Embedded SW Engineer I - Digital Twin
Summary
Develops and validates digital twin software for automotive systems, simulating vehicle electronics and ensuring feature conformance using C/C++, embedded Linux/QNX, and automotive protocols like CAN/Ethernet.
The Embedded SW Engineer will work in the Digital Twin workstream, focused on virtualizing the vehicle's electronic architecture and validating features and system behaviors.
Working Experience
3 or more years of hands-on experience in embedded software engineering, ideally in an automotive or safety-critical environment.
Responsibilities
- Analysis and implementation of software requirements and tasks.
- Design, coding, configuration, testing, and documentation of digital twin for different domains.
- Technical contact for the global software development team.
- Testing of software functions in hardware and software simulation environments to ensure conformance with customer requirements.
- Debugging and troubleshooting software.
Qualifications
- Proficiency in C and C++ for embedded software development.
- Knowledge of the Software Development Lifecycle.
- Hands-on experience with Embedded Linux or QNX.
- Knowledge of Ethernet protocols such as TCP/IP.
- Experience in CAN bus, including setup, configuration, and troubleshooting.
- Familiarity with virtualized ECU environments or virtual hardware-in-the-loop setups.
- Experience on Software integration using Change and Requirement management tools (i.e. ALM, JIRA, GIT)
- Candidate must be proficient in English level, since will be part of a global team. Meetings, mailing and communication uses English.
Desired
- Experience with QNX specifically in an ADAS or high-performance compute context.
- Knowledge of Ethernet automotive protocols such as SOME/IP or DDS for ECU interconnection.
- Familiarity with hypervisor technologies.
- Experience writing system-level tests covering integration, communication, and functional validation.
- Exposure to sensor simulation frameworks for camera and radar virtualization.
- Understanding of vehicle dynamics modeling or simulation environments.
- Understanding of AUTOSAR Classic architecture, including RTE, BSW layers, and COM stack.
- Basic understanding of ADAS perception pipelines.
- Knowledge on RUST
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