Job summary
This role involves validating and adapting an edge AI hardware and software solution for the automotive market. The engineer will translate automotive requirements into testing criteria, port and optimize AI workloads, benchmark system performance against automotive use cases, and contribute to safety-qualified software development. Collaboration with cross-functional teams and participation in industry R&D projects are key aspects.
Location and work setup
- Location
- Norway
- Work setup
- Remote
Responsibilities
Translate automotive market and customer needs into evaluation criteria and verify the AI stack accordingly. Port, quantize, and optimize automotive AI workloads, developing benchmarks under realistic conditions and comparing against competitors. Identify gaps between current software and automotive requirements and prototype runtime integration with automotive-specific operating systems and middleware. Contribute to safety-related software components following ASIL-B/ASIL-D standards, supporting functional safety verification. Lead technical work packages in collaborative R&D efforts and monitor automotive AI trends to inform product and engineering priorities.
Qualifications
4 to 8 years experience in embedded software or application engineering within automotive or automotive semiconductor industries. Proficient in embedded C and Python tooling/test automation. Experience with real-time systems and safety-certified development (ASIL-B/ASIL-D, ISO 26262). Skilled in embedded Linux and automotive toolchains, with exposure to QNX and AUTOSAR environments. Experienced in hardware validation, benchmarking, and documentation. Strong requirements-driven development mindset and fluent in English. Familiarity with AI frameworks, automotive perception workloads, and automotive safety/quality standards is advantageous but not mandatory.