מציאת משרת הייטק בחברות הטובות ביותר מעולם לא הייתה קלה יותר
Apple AIML - Senior Embedded Machine Learning Engineer- Edge ML United States, Washington, Seattle 58047217
Yesterday
You will play a key role in designing, implementing, and optimizing ML solutions for highly constrained compute environments. This is a cross-disciplinary role that blends expertise in embedded systems, computer architecture, and machine learning to unlock new applications in areas such as IoT, wearables, robotics, and autonomous systems.RESPONSIBILITIES:- Design and implement embedded ML pipelines on microcontrollers and custom SoCs with tight compute, memory, and power constraints.- Optimize and quantize deep learning models for real-time inference on edge platforms.- Develop and maintain low-level firmware in C/C++ to integrate ML models with custom hardware accelerators and sensors.- Conduct performance benchmarking, memory profiling, and bottleneck analysis across various embedded platforms.- Collaborate closely with ML researchers, hardware architects, and product engineers to co-design efficient ML solutions from model training to deployment.- Evaluate new edge ML techniques, compilers (e.g., TVM, TFLite Micro, CMSIS-NN), and toolchains to advance the team's capabilities.- Contribute to the overall system architecture with a deep understanding of embedded compute, memory hierarchies, and data flow optimization.
- Strong proficiency in C/C++ and Python, with a solid foundation in embedded firmware development.
- Deep understanding of computer architecture, particularly ARM Cortex-M/A cores, SIMD, caches, memory alignment, and DMA usage.
- Proficiency in model deployment tools and compilers such as TensorFlow Lite for Microcontrollers, TVM, ONNX Runtime, and custom model conversion pipelines.
- Demonstrated expertise in performance analysis, using tools like perf, valgrind, gprof, or hardware-specific profilers.
- Experience working with hardware interfaces such as SPI, I2C, UART, and integrating with sensors or custom accelerators.
- Bachelor's, Master's, or PhD or equivalent experience in Computer Science or a related field.
- Hands-on experience with deep learning concepts, including model architectures (CNNs, RNNs, Transformers), training workflows, and post-training optimization (quantization, pruning, distillation).
- Familiarity with embedded RTOSes (e.g., FreeRTOS, Zephyr) and real-time application constraints.
- Comfort with debugging low-level issues across software and hardware boundaries.
- Excellent problem-solving and analytical skills with a thorough approach.
- Most importantly: a strong curiosity, willingness to dive deep into unfamiliar problems, and an eagerness to learn and grow in a fast-evolving field.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
משרות נוספות שיכולות לעניין אותך
