Video QA Engineer

Key Responsibilities

• Perform end-to-end validation of video capture, encoding, decoding, playback, and streaming use cases on Snapdragon-based devices.

• Test and triage issues across Video Codec (VENC/VDEC), Camera-Video pipeline, Display, and multimedia frameworks (StageFright, Codec2.0).

• Validate performance KPIs: frame rate, latency, thermal behavior, bitrate stability, quality metrics (PSNR/SSIM/VMAF).

• Execute and enhance automated video test suites (Python/ADB/Test frameworks).

• Analyze logs and debug using:

• QXDM

• systrace/perfetto

• logcat/kmsg

• mm_qcamera, mm_codec logs

• Validate video behavior under corner cases: stress, concurrency, thermal throttling, power collapse, low-memory conditions.

• Work with development teams to deliver root-cause analysis for video pipeline issues.

• Ensure compliance with video standards: H.264, HEVC, AV1, VP9, HDR10/HLG, and DRM restrictions.

• Support test planning for new SoC bring-up, BSP drops, OEM programs, and regression cycles.

Required Skills

• Strong understanding of video codec fundamentals: encoding/decoding, GOP, rate control, motion estimation.

• Experience with Android multimedia frameworks and HAL layers.

• Hands-on debugging of:

• crashes

• ANRs

• video freezes/dropped frames

• synchronization issues (A/V sync)

• Proficiency with testing tools: ffmpeg, VLC, GStreamer, adb, QXDM.

• Knowledge of camera-video integration, metadata flow, and buffer pipelines (ION/Gralloc).

• Good exposure to Python or shell scripting for automation.

Good to Have

• Experience with MM SysArch, Camera HAL3, or Display pipeline (MDSS).

• Exposure to performance profiling tools (Perfetto, Trepn, Snapdragon Profiler).

• Understanding of HDR, WCG, 10-bit encoding, Dolby Vision workflows.

• Familiarity with AI-based video enhancement models.

• OEM or product launch experience.