Embedded Signal Processing and ML Algorithms Engineer

Join Apples Human Interface Design (HID) team to develop advanced sensing tracking and classification algorithms to enable best-in-class user experiences across Mac iPhone iPad Apple Pencil Apple Watch and exciting new products. We are looking for a strong machine learning u0026 DSP engineer with a passion for bridging algorithm development with embedded system design and software integration and leveraging GenAI tools into an engineering workflow. Our team brings togethers experts of diverse backgrounds: Machine Learning Signal Processing Firmware Software Physics Mathematics Human Factors and more. You will work at the intersection of hardware software and design collaborating with specialists across Apple to ship extraordinary products used every day by millions of people around the world.

This is an machine learning engineering role at the HW/SW/UI boundary with broad collaboration opportunities across firmware software and algorithms teams. You will be responsible for developing sensing algorithms using signal processing and machine learning techniques and delivering them as highly optimized power-efficient code for custom silicon. Youll tackle complex challenges like memory constraints computational budgets and real-time performance while ensuring robust end-to-end functionality from sensor data acquisition through to the software layer to deliver exceptional user this role you will also lead efforts to identify evaluate and deploy GenAI tools that improve team productivity including GenAI-assisted development data analysis and workflow automation. You will help define best practices for GenAI tool adoption within the group and collaborate cross-functionally to scale these efforts.

Prototype and develop sensing tracking and classification algorithms to support new product form factors and new user-facing featuresnDevelop and integrate robust C/C low-level software for deploying algorithms on microcontrollers DSPs and ML acceleratorsnIntegrate algorithm implementations with the SW layer ensuring correctness performance and stability across product configurationsnWork with firmware and software engineers throughout the product lifecycle from early prototyping through productizationnDevelop and maintain integration test frameworks and performance metrics to validate algorithm behavior end-to-endnProfile and budget algorithm compute/memory workloads on embedded platforms to guide silicon architecture teams on accelerator requirements core selection and memory sizing for future hardwarenIdentify and champion GenAI tools and developer productivity solutions that can be adopted within the teamnEvaluate GenAI-assisted workflows (e.g. code generation data analysis automated testing) and driving their integration into team processesnCommunicate findings integration status and tooling recommendations clearly to team members and leadership

Bachelors degree in Electrical Engineering Computer Engineering Computer Science or related technical field and 3 years of relevant industry experience nStrong software programming skills in C/C Python and experience with embedded systemsnStrong background in signal processing machine learning and statistical learning algorithmsnExperience with object-oriented programming and common software design patternsnExperience leveraging AI-powered development tools to streamline daily workflows accelerate coding and debugging creating test frameworks and improve overall code quality and testingnExcellent communication presentation and documentation skills

Masters/PhD degree with 3 years of experience in algorithm integration or embedded/software systemsnProven track-record in signal processing and machine learning including areas such as 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 plusnFamiliar in C/C for embedded systems development including RTOS microcontrollers and low-level hardware interactions nUnderstanding of modern SoC/ASIC architectures hardware neural/math accelerators memory-bandwidth bottlenecks and experience with HW/SW partitioning for complex algorithms is a strong plusnExperience working at the HW/SW interface including familiarity with firmware interfaces driver layers or OS-level integrationnHands-on experience prototyping developing and integrating algorithm and signal processing code with software layer (e.g. OS-level frameworks or application software)nTrack record of evaluating integrating and deploying AI-powered developer tools (e.g. LLM-assisted coding AI-based test generation intelligent data analysis pipelines)nStrong cross-functional collaboration skills with the ability to work effectively across firmware software and algorithms disciplines