System Modeling & Integration Engineer
Core
Hands-on integration, debugging, optimization, and validation of ADAS algorithms on real embedded hardware for production automotive ECUs.
Role type
Senior IC ADAS Algorithm Integration Engineer
Builds
Production-ready ADAS platforms integrating perception, fusion, localization, and planning algorithms
Domain
Automotive ADAS (Advanced Driver Assistance Systems) and Embedded Systems
Deliverable
production ML models
Required skills
ADAS perception and planning pipelines, embedded memory and timing optimization, C/C++ and Python, AUTOSAR (Classic/Adaptive) and QNX, debugging complex automotive ECUs, SIL/HIL and vehicle testing environments
Preferred skills
Camera, radar, and lidar sensor integration, middleware (DDS, SOME-IP, RTPS), ISO 26262, ASPICE, automotive cybersecurity, Git, Jenkins, CMake/Bazel
Technologies
AUTOSAR OS, QNX, Trace32, Vector CANoe/CANalyzer, GDB, QNX Momentics
Responsibilities
Integrate perception, fusion, localization, and planning algorithms into automotive ADAS platforms; Independently analyze algorithm data flows, state machines, and outputs to debug functional and performance issues; Redesign memory layouts, buffers, stack/heap usage, and partitioning to fit PoC algorithms into production ECUs; Analyze and optimize RAM/ROM usage, cache behavior, memory bandwidth, and DMA strategies; Investigate timing overruns, jitter, latency, and execution bottlenecks; Optimize scheduling, task priorities, and IPC using AUTOSAR OS or QNX
Seniority
Senior, hands-on IC