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

About this role

Applied Intuition seeks an Embedded AI Engineer to develop on-device intelligence for Android Automotive, managing the full lifecycle of production ML systems optimized for real-world constraints like latency, thermal limits, and safety. You'll deploy multimodal LLMs, integrate ML inference frameworks, and design safety guardrails for vehicle-integrated AI.

What you'll do

• Deploy production ML inference and learning systems on Android Automotive (AAOS)
• Implement on-device multimodal LLMs with schema design and safe vehicle API dispatch
• Integrate models using TensorFlow Lite, ONNX Runtime, or vendor SDKs
• Profile and optimize models for latency, memory, power, and thermal budgets
• Design safety boundaries and guardrails for model outputs with fallback logic
• Interface with vehicle signals, sensors, and system services using C++ and JNI

What they're looking for

• C++ and native Android integration (JNI)
• ML inference on embedded and mobile platforms
• Model optimization (quantization, pruning, compilation)
• LLM function calling and tool execution
• Android Automotive OS (AAOS) system services
• Edge computing constraints and real-time behavior
• Performance instrumentation across CPU, GPU, and NPU
• Multimodal LLM deployment

Benefits

• Competitive base salary ($150,000–$250,000 USD annually)
• Equity compensation (stock options/RSUs)
• Comprehensive health, dental, vision, life, and disability insurance
• 401(k) retirement plan with employer match
• Learning and wellness stipends
• Paid time off