Embedded Machine Learning Engineer
Apple
Full-time
On-site
Seattle, Washington, United States
Machine Learning
This role offers a unique opportunity to innovate at the intersection of AI and embedded hardware. You will transform advanced ML algorithms into highly optimized, power-efficient code for custom silicon and microcontrollers in Apple products, specifically for robotics. You'll tackle complex challenges like memory constraints, computational budgets, and real-time performance, ensuring ML models deliver exceptional user experiences while adhering to Apple’s privacy and power efficiency standards.
- Bachelor’s degree (3+ years experience) or Master’s degree (1+ year experience) in CS, EE, or a related technical field.
- Proficiency in C/C++ for embedded systems development, including RTOS, microcontrollers, and low-level hardware interactions.
- roven ability to optimize and deploy ML models for resource-constrained edge devices using techniques like - quantization/pruning and frameworks (e.g., TensorFlow Lite, ONNX Runtime, Core ML).
- Strong analytical and debugging skills to resolve performance bottlenecks across hardware, firmware, and ML inference.
- Experience with ML inference hardware acceleration (DSPs, NPUs, ASICs).Familiarity with diverse neural network architectures and training methodologies for efficient edge deployment.
- Knowledge of computer vision, NLP, or audio processing in an embedded/robotics context.
- Experience with embedded Linux or other RTOS in a production environment.
- Contributions to open-source embedded ML projects or relevant publications.
- Proficiency with Python for automation and data analysis.