14 дней назад
Group Lead Edge AI
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Group Lead Edge AI (Robotics/Embedded AI): Leading the development of on-device intelligence for robots, from research through production deployment, with an accent on model optimization, embedded accelerator platforms, and end-to-end inference toolchains. Focus on building the engineering team, benchmarking performance across hardware targets, and solving quantization, latency, memory, and accuracy challenges on embedded systems.
Location: On-site in Metzingen / Riederich, Germany
Company
develops robot behaviors powered by on-device intelligence.
What you will do
- Own the roadmap for taking edge AI from research to shipped products.
- Hire, mentor, and develop a team of edge AI engineers.
- Deploy and optimize models on embedded accelerator platforms such as NVIDIA Jetson and Qualcomm IQ-series.
- Own the model export, inference optimization, and deployment toolchain, including ONNX, TensorRT, AIMET, and relevant SDKs.
- Collaborate with Hardware, Software, and Product teams within latency, power, and memory budgets.
- Lead benchmarking, on-device evaluation, performance regression testing, and hands-on debugging.
Requirements
- Master's degree or PhD in Computer Science, Electrical Engineering, Embedded Systems, or a related field.
- 7+ years of ML or embedded AI engineering experience, including 2+ years of technical leadership and production deployment on embedded accelerators.
- Hands-on experience with embedded AI hardware platforms such as NVIDIA Jetson, Qualcomm IQ-series, or comparable systems.
- Expertise in quantization, pruning, distillation, architecture search, and model deployment toolchains.
- Strong Python, C++, PyTorch, embedded Linux, and low-level profiling skills.
- Professional English is required; German at B2–C1 level is a strong plus.
Culture & Benefits
- Hands-on technical leadership across research, hardware, software, and product development.
- Ownership of technical direction and engineering quality standards.
- Work focused on production-grade, on-device intelligence for robotic systems.
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