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

📋 Description

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

🎯 Requirements

• 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
• Hands-on experience with Android system services or Android Automotive OS (AAOS)

🎁 Benefits

• Health, dental, vision, life and disability insurance
• 401(k) retirement benefits with employer match
• Learning and wellness stipends
• Paid time off
• Equity in stock options or RSUs