Software Development Engineer in Test (Android Audio)

Overview

Dolby is looking for passionate new graduates and junior engineers to join our Android audio integration test team.

In this role, you will work at the intersection of cutting-edge audio technology and mobile software engineering - helping to ensure that Dolby's world-class audio algorithms perform flawlessly on Android devices.

You'll design and build test systems that scale, and you'll have the opportunity to shape how AI-powered tools transform the way we test.

Responsibilities

1. Test Audio Algorithm Integration

• Validate the integration of Dolby audio algorithms into Android mobile platforms, ensuring correctness, performance, and reliability across diverse devices.
• Analyze requirements, system behavior, and potential risk areas to design comprehensive test cases with clear functional coverage and boundary conditions.
• Implement and maintain automated test scripts and frameworks to accelerate test execution.
• Maintain clear test documentation, report defects with precision, and communicate test results to stakeholders.

• Evaluate and integrate emerging AI tools and methodologies to improve test efficiency, anomaly detection, and coverage analysis.

• Work closely with integration developers, PMs, audio algorithm engineers, support engineers and QA leads to discuss schedules, identify gaps, reproduce issues, and drive quality improvements.

• Bachelor's degree or higher in Computer Science, Electrical Engineering, Audio Engineering, or a related field - new graduates welcome.
• Foundational knowledge of the Android audio stack and multimedia frameworks.
• Hands-on experience writing Python scripts for automation, data processing, or testing.
• Curiosity and a growth mindset - eager to learn new tools, frameworks, and domains quickly.
• Excellent English communication skills (written and verbal) for seamless collaboration with global R&D teams.

• Experience with Android development tools (ADB, Android Studio, Logcat, etc.).
• Basic understanding of Digital Signal Processing (DSP) concepts, such as filtering, frequency domain analysis.
• Exposure to AI/ML frameworks (e.g., TensorFlow, PyTorch) or AI-assisted testing tools.
• Experience with test frameworks such as pytest, unittest, or Android Instrumentation.
• Familiarity with CI/CD pipelines and version control (Git).

• Academic or personal projects involving audio processing, signal analysis, or mobile development.
• Contributions to open-source testing or audio-related projects.
• Experience with audio quality evaluation tools or perceptual audio metrics.