Embedded Signal Processing and ML Algorithms Engineer

Apple • San Diego, CA

9d

About The Position

Join Apple's Human Interface Design team to develop advanced sensing, tracking, and classification algorithms for user experiences across Mac, iPhone, iPad, Apple Pencil, Apple Watch, and new products. This machine learning engineering role operates at the hardware, software, and user-interface boundary, collaborating broadly with firmware, software, and algorithms teams.

Develop sensing algorithms using signal processing and machine learning, then deliver them as highly optimized, power-efficient code for custom silicon. Address memory constraints, computational budgets, real-time performance, and end-to-end functionality from sensor data acquisition through the software layer. Lead efforts to identify, evaluate, and deploy generative AI tools for engineering productivity, including development assistance, data analysis, and workflow automation. Help define adoption best practices and collaborate cross-functionally to scale these efforts.

Requirements

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field, and 3 years of relevant industry experience.
• Strong software programming skills in C/C++ and Python, with experience in embedded systems.
• Strong background in signal processing, machine learning, and statistical learning algorithms.
• Experience with object-oriented programming and common software design patterns.
• Experience using AI-powered development tools to streamline workflows, accelerate coding and debugging, create test frameworks, and improve code quality and testing.
• Excellent communication, presentation, and documentation skills.

Nice To Haves

• Master’s or PhD degree with 3+ years of experience in algorithm integration or embedded/software systems.
• Proven track record in signal processing and machine learning, including time-series analysis, digital filtering, feature extraction, classification, regression, or neural network-based inference; experience applying these techniques to sensor data or embedded sensing systems is a strong plus.
• Familiarity with C/C++ embedded systems development, including RTOS, microcontrollers, and low-level hardware interactions.
• Understanding of modern SoC/ASIC architectures, hardware neural/math accelerators, memory-bandwidth bottlenecks, and hardware/software partitioning for complex algorithms is a strong plus.
• Experience at the hardware/software interface, including familiarity with firmware interfaces, driver layers, or OS-level integration.
• Hands-on experience prototyping, developing, and integrating algorithm and signal-processing code with a software layer, such as OS-level frameworks or application software.
• Track record of evaluating, integrating, and deploying AI-powered developer tools, such as LLM-assisted coding, AI-based test generation, or intelligent data-analysis pipelines.
• Strong cross-functional collaboration skills and ability to work effectively across firmware, software, and algorithms disciplines.

Responsibilities

• Develop sensing algorithms using signal processing and machine learning techniques.
• Deliver algorithms as highly optimized, power-efficient code for custom silicon.
• Address memory constraints, computational budgets, and real-time performance requirements.
• Ensure robust end-to-end functionality from sensor data acquisition through the software layer.
• Identify, evaluate, and deploy GenAI tools to improve team productivity, including development assistance, data analysis, and workflow automation.
• Help define best practices for GenAI tool adoption and collaborate cross-functionally to scale these efforts.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level