Embedded AI Engineer – Android Automotive (On-Device Intelligence)

Job summary

Responsibilities

We are building on-device intelligence for a next-generation Android Automotive platform. This role owns the end-to-end lifecycle of embedded ML systems, ensuring models behave predictably and safely in production environments under real-world constraints such as latency, thermal limits, and…

• Deploy and run production-grade ML inference and learning systems on Android Automotive (AAOS)
• Implement on-device multimodal LLMs, including schema design and safe dispatch to local vehicle APIs
• Integrate models using TensorFlow Lite, ONNX Runtime, or specialized vendor SDKs
• Profile and optimize models for strict latency, memory, power, and thermal budgets
• Instrument runtime performance across CPU, GPU, and NPU acceleration layers

What they're looking for

• BS, MS, or PhD in Computer Science, Electrical Engineering, or a related technical field
• 3+ years of experience shipping ML inference on embedded, mobile, or automotive platforms
• Strong proficiency in C++ and experience with native Android integration (JNI)
• Expertise in model optimization techniques such as quantization, pruning, and compilation
• Experience integrating LLM function calling or tool execution with structured outputs

Tech stack

• TensorFlow
• C++
• Transformers