AIML - Sr Embedded Machine Learning Engineer, Edge ML & Ultra-Constrained Compute

Apple Inc.; Seattle (WA); On-site; USD 100,000 - 160,000; Full time

Job summary

An established industry player is seeking a Senior Embedded Machine Learning Engineer to innovate in the field of edge ML. This role involves designing and optimizing machine learning solutions for constrained environments, focusing on applications in IoT, robotics, and autonomous systems. You will work with cutting-edge technologies, collaborate with experts across disciplines, and contribute to the development of efficient ML pipelines. If you're passionate about embedded systems and eager to tackle complex challenges, this opportunity is perfect for you to grow and make a significant impact in a fast-evolving field.

Qualifications

• Strong proficiency in C/C++ and Python for embedded firmware development.
• Deep understanding of computer architecture and performance analysis tools.

Responsibilities

• Design and implement embedded ML pipelines on microcontrollers.
• Collaborate with ML researchers and hardware architects for efficient ML solutions.

Skills

C/C++

Python

Embedded Firmware Development

Performance Analysis

Machine Learning

Debugging

Education

Bachelor's in Computer Science

Master's in Computer Science

PhD in Computer Science

Tools

TensorFlow Lite

TVM

ONNX Runtime

perf

valgrind

gprof

Job description

AIML - Senior Embedded Machine Learning Engineer- Edge ML

Seattle, Washington, United States Machine Learning and AI

Description

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:

1. Design and implement embedded ML pipelines on microcontrollers and custom SoCs with tight compute, memory, and power constraints.
2. Optimize and quantize deep learning models for real-time inference on edge platforms.
3. Develop and maintain low-level firmware in C/C++ to integrate ML models with custom hardware accelerators and sensors.
4. Conduct performance benchmarking, memory profiling, and bottleneck analysis across various embedded platforms.
5. Collaborate closely with ML researchers, hardware architects, and product engineers to co-design efficient ML solutions from model training to deployment.
6. Evaluate new edge ML techniques, compilers (e.g., TVM, TFLite Micro, CMSIS-NN), and toolchains to advance the team's capabilities.
7. Contribute to the overall system architecture with a deep understanding of embedded compute, memory hierarchies, and data flow optimization.

Minimum Qualifications

• 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.

Preferred Qualifications

• 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.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.