Back to search
Description
In this role you will own the end-to-end audio systems architecture spanning silicon, firmware, kernel drivers, and the user-space frameworks that power every Apple product. You'll partner deeply with silicon, EE, acoustics, ML, and framework teams to make the architectural calls that define audio on Apple platforms several years out — from clocking and DMA topology on next-generation SoCs, through secure firmware partitioning, all the way up to the APIs that third-party developers build on. This is a hands-on architect role: you'll prototype, write code, lead deep-dive investigations into systemic issues, and convert those findings into durable architectural fixes. We are looking for someone who is a force multiplier — an engineer who has materially adopted AI-assisted engineering into their daily practice and can show concrete examples of where coding agents, LLM-driven analysis, and tool-calling workflows have changed how they work. You will be expected not only to use these tools fluently yourself, but to identify the highest-leverage workflows for the broader audio organization, prototype them, and drive their adoption across firmware, driver, and framework teams.
Minimum Qualifications
BS in Computer Science, Electrical Engineering, or equivalent industry experience 10+ years of relevant engineering experience, with demonstrated ownership of cross-stack architecture spanning silicon, firmware, drivers, and OS frameworks Excellent programming skills in C and C++, with strong fundamentals in OOP, real-time systems, and low-level performance Strong understanding of multi-core SoC architecture, DMA, interrupt handling, power management, and RTOS internals Hands-on experience with audio fundamentals: sample rates, clocking, buffering, latency, I2S/TDM/SoundWire, PCM/PDM, codecs, and DSP pipelines. Comfortable reviewing hardware schematics and partnering with EE and silicon design teams on register-level interfaces and pre-silicon validation. Proven track record of leading technical design from concept through mass production across multiple product lines simultaneously. Excellent written and verbal communication skills, with the ability to align executives, peer architects, and individual contributors on a shared technical direction.
Preferred Qualifications
MS or PhD in Computer Science, Electrical Engineering, or related field. Proven experience designing, building, and deploying AI-driven automated workflows and tools in a production engineering context. Experience using LLMs and autonomous agents to solve complex engineering problems — code generation, log and trace analysis, automated triage, large-scale refactors. Hands-on experience developing custom "skills" and tool-calling capabilities for AI agents to interact with APIs, databases, build systems, and internal software frameworks. Familiarity with on-device ML inference paths and audio ML features (speech, noise control, spatial audio). Experience with secure firmware environments, exclaves, or other trusted execution domains on embedded SoCs. Track record of building tools, automation, or internal infrastructure that scaled the impact of teams beyond your direct contributions. Ability to identify and develop solutions to broad, systemic problems across complex hardware and software environments. Ability to thrive in a fast-paced, ambiguous environment and make sound decisions with incomplete information.
Learn more about this Employer on their Career Site
