Director Engineering - AI software stack
Core
Define and own the AI/ML technology roadmap for automotive and edge AI platforms, driving adoption of LLMs, VLMs, and agentic AI systems for safety-critical deployments.
Role type
Director Engineering - AI software stack
Builds
End-to-end AI systems from research to production, including model onboarding, optimization, validation, and lifecycle management.
Domain
Automotive and edge AI platforms
Deliverable
production ML models
Required skills
AI/ML system design, LLMs/VLMs/multimodal AI, heterogeneous compute optimization (CPU/GPU/DSP/NPU), model optimization (quantization, compression, batching), team leadership, technical strategy
Preferred skills
Automotive or industrial platforms, embedded Linux/QNX, real-time constraints, QNN-like runtimes, inference SDKs, GenAI fine-tuning, reinforcement learning, software architecture
Technologies
PyTorch, TensorFlow, ONNX, C, C++, Java, Python, embedded Linux, QNX
Responsibilities
Define AI/ML technology roadmap aligned with business goals, drive adoption of LLMs and agentic AI systems, influence platform and silicon-level decisions, oversee end-to-end delivery of AI systems, build and mentor multi-disciplinary AI/ML engineering teams, set technical direction and career growth paths
Seniority
Director, strategy & mentorship
