Integrate audio software with DSP frameworks, OS services, HALs, and hardware interfaces.
Analyze issues across application framework, middleware, HAL, OS, DSP, and hardware layers.
Support platform bring-up, integration, validation, and customer-specific audio configurations.
Prepare and review high-level and low-level software designs, including UML-based designs.
Perform unit testing with Google Test/GTest and contribute to CI/CD activities.
Participate in design and code reviews and promote clean-code and software-quality practices.
Provide technical guidance and support cross-functional teams in resolving complex audio issues.
Requirements
B.E., https://jobeax.com/link/2DENLGgQM7whDhaE, M.E., or https://jobeax.com/link/s1WvHFV9ITSwCkyS in Computer Science, Electronics, Electrical, Telecommunication, or a related engineering discipline.
5–9 years of experience in relevant software development.
Strong C++ 11/14/17 programming skills and understanding of object-oriented design, STL, memory management, multithreading, concurrency, and synchronization.
Hands-on QNX development experience on embedded systems, including QNX audio middleware or audio-management components.
Good understanding of automotive audio routing, streaming, device handling, low-latency audio, amplifiers, and DSP integration.
Hands-on experience with AOSP/Android Audio Framework and components including AudioFlinger, AudioPolicyManager, AudioPolicyService, AudioManager, AudioService, Car Audio Framework, Audio HAL, AIDL, and HIDL.
Strong Android debugging skills using logcat, bug reports, and Tombstone logs.
Understanding of embedded systems and RTOS concepts.
Experience with Qualcomm automotive audio architecture and DSP frameworks is preferred.
Experience with hypervisor-based IVI architecture is preferred.
Hands-on knowledge of QACT, QXDM, and Qualcomm ACDB is preferred.
Knowledge of I2S, audio DSP processing, effects, tuning, and CAN/vehicle signals influencing audio behavior is preferred.
Experience with UML/design tools and software design patterns is preferred.
Familiarity with ISO 26262 and secure software development practices is preferred.
Exposure to GitHub Copilot, LLMs, AI Agents, or agentic workflows is an additional advantage.
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