Tasks:
- * Adapt software for heterogeneous computing platforms
- * Build multi-sensor calibration tools and algorithms
- * Build performance benchmarks and automated regression testing
- * Build robot software frameworks and system interfaces
- * Debug system issues and document engineering processes
- * Deploy and accelerate AI models on edge platforms
- * Develop and optimize DDS/ROS 2 middleware
- * Develop Linux and RTOS drivers and system software
- * Develop robot agent applications and task workflows
- * Develop ROS/ROS 2 sensor nodes and sensor fusion integrations
- * Develop sensor drivers and data pipelines
- * Integrate hardware-to-application software stacks
- * Integrate LLM/VLM capabilities with robot systems
- * Integrate perception, motion control, and AI inference
- * Profile and optimize embedded system performance
Perks/Benefits:
Skills/Tech stack required:
[AI Inference] [AI Inference Optimization] [ARM architecture] [C#] [C++] [CUDA] [DDS] [Device Drivers] [DMA] [Function Calling] [I2C] [Inference Optimization] [Linux] [Linux device drivers] [Model Quantization] [Multithreaded programming] [Network Programming] [ONNX] [OpenCL] [PCIe] [Python] [PyTorch] [QNN] [RAG] [ROS 2] [RTOS] [Sensor Calibration] [SLAM] [SPI] [System profiling] [TensorFlow Lite] [TensorRT] [UART]
Educational requirements:
[Bachelor's Degree] [Master's Degree]
Role(s):
[AI Software Engineer] [Embedded Software Engineer] [Embedded Systems Engineer] [Engineer] [Middleware Engineer] [Robotics Software Engineer] [Software Engineer] [Systems Engineer]